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Transport spatial model for the definition of green routes for city logistics centers
Abstract
This paper presents a transport spatial decision support model (TSDSM) for carrying out the optimization of green routes for city logistics centers. The TSDSM model is based on the integration of the multi-criteria method of Weighted Linear Combination (WLC) and the modified Dijkstra algorithm within a geographic information system (GIS). The GIS is used for processing spatial data. The proposed model makes it possible to plan routes for green vehicles and maximize the positive effects on the environment, which can be seen in the reduction of harmful gas emissions and an increase in the air quality in highly populated
areas. The scheduling of delivery vehicles is given as a problem of optimization in terms of the parameters of: the environment, health, use of space and logistics operating costs. Each of these input parameters
was thoroughly examined and broken down in the GIS into criteria which further describe them. The model presented here takes into account the fact that logistics operators have a limited number of environmentally
friendly (green) vehicles available. The TSDSM was tested on a network of roads with 127 links for the delivery of goods from the city logistics center to the user. The model supports any number of available
environmentally friendly or environmentally unfriendly vehicles consistent with the size of the network and the transportation requirements.
... In problems that involve routing on transportation networks, it is often desirable to choose routes according to multiple criteria, such as distance, travel time, and comfort, and Multi-Criteria Decision-Making (MCDM) has become increasingly popular in this domain [6,11,12]. Multi-criteria are combined to generate weightings, which are then fed into a standard shortest path algorithm, such as Dijkstra's algorithm or A* [6]. ...
... Pamucar et al. [12] demonstrated an alternative approach using Weighted Linear Combination (WLC) of raster datasets, a tool commonly used in GIS [14]. In this method, the raster cells are transformed (normalised) so that the units are standardised between the datasets. ...
... After normalisation, each raster cell is multiplied by its assigned criteria weight, and then each raster layer has its corresponding cell added to WSM (Figure 3). The bi-linear interpolation is then used to convert the average of the cell to the line (road) segment [12]. Pamucar et al. [12] used 21 different criteria to propose routes for more and less environmentally friendly vehicles to improve air quality in populated areas. ...
Creating routes across open areas is challenging due to the absence of a defined routing network and the complexity of the environment, in which multiple criteria may affect route choice. In the context of urban environments, research has found Visibility and Spider-Grid subgraphs to be effective approaches that generate realistic routes. However, the case studies presented typically focus on plazas or parks with defined entry and exit points; little work has been carried out to date on creating routes across open areas in rural settings, which are complex environments with varying terrain and obstacles and undefined entry or exit points. To address this gap, this study proposes a method for routing across open areas based on a Spider-Grid subgraph using queen contiguity. The method leverages a Weighted Sum–Dijkstra’s algorithm to allow multiple criteria such as surface condition, total time, and gradient to be considered when creating routes. The method is tested on the problem of routing across two areas of Dartmoor National Park, United Kingdom. The generated routes are compared with benchmark algorithms and real paths created by users of the Ordnance Survey’s Maps App. The generated routes are found to be more realistic than those of the benchmark methods and closer to the real paths. Furthermore, the routes are able to bypass hazards and obstacles while still providing realistic and flexible routes to the user.
... Gupta et al. (2017) considered carbon monoxide emissions due to long-term damage to the ozone layer. In addition to carbon dioxide emissions, other studies considered nitrogen monoxide, nitrogen dioxide, sulphur dioxide and other harmful gases and Pamucar et al. (2016)). The amount of harmful gases is assumed to be a ratio of total fuel consumption. ...
... The risk of transporting infectious medical waste was studied by Hachicha et al. (2014) and the accident risk of other dangerous goods transport was studied by Alexiou and Katsavounis (2015). Air pollution-related diseases and sound levels permitted by legal authorities were studied by Pamucar et al. (2016). Employment opportunities associated with new facilities were studied by Ouhader and El Kyal (2017). ...
... Hachicha et al. (2014) carried out studies on the problem of infectious waste collection, where Alexiou and Katsavounis (2015) concentrated on transporting dangerous goods. Pamucar et al. (2016) studied finding less dangerous routes. In the "other" category, Ozdamar et al. (2004) studied unfulfilled demand minimization, while Osvald and Stirn (2008) focused on maintaining the freshness of perishable food products. ...
The challenges of simultaneous profit maximization and environmental or social externality mitigation need to be urgently addressed by companies. Accordingly, attention to the Sustainable Vehicle Routing Problem incorporating economic, environmental, and social concerns has been gradually increasing. To the best of our knowledge, this is the first literature review that focuses on sustainability practices in urban routing. Our first objective is to investigate the scopes, objectives, solution methodologies, and data types in the reviewed papers. The second objective is to analyse the indicators used in the proposed quantitative models and how they are related to sustainability and green criteria in the vehicle routing field. These criteria are adapted from Elkington's (2001) triple bottom line (TBL) approach that emphasizes economic, environmental, and social dimensions. The final objective is to examine the findings of the studies, identify gaps in the related literature, and suggest directions for future research. One of the key findings of this study is that the economic dimension is the prominent driver among the three pillars of sustainability. The researchers relatively less address the environmental and social dimensions. It is determined that the social indicators are the least studied sub-dimension of sustainability. The results of this study are thought to help researchers and practitioners to learn more about the methods and models of sustainability or green practices, the metrics used, and the economic, environmental, and social results.
... All activities toward improving mobility in urban areas are associated with city-logistics which aims to organize effective freight transport in the city and reduce the nuisance associated with this transport at the same time. City-logistics is set mostly to support the economic and social development of cities and to keep the business operating safely and efficiently in close proximity of human settlements [40]. The city-logistics is not only interested in goods but also considers passengers' movement due to their daily needs since passenger and goods traffic are very mixed in urbanized areas. ...
... In many publications on planning transport in urban agglomerations, the so-called urban logistics centres supporting freight transport in cities are proposed as an indirect solution to mobility issues [40,46,53]. Other publications focus on the composition of the fleet of public transport vehicles optimally meeting requirements and interacting with the environment [23]. ...
... Other publications focus on the composition of the fleet of public transport vehicles optimally meeting requirements and interacting with the environment [23]. In [40] and [28], the authors present models that enable route planning for vehicles while maximizing their positive impact on the environment. Using these models helps to reduce harmful gas emissions and improve air quality in areas with high population density. ...
The paper presents decision problems related to the development of transport systems facing planning challenges of sustainable urban mobility. Currently, city decision-makers must deal with growing difficulties related to the organisation of public transport systems. These difficulties involve the primary need for effective and ecological public transport systems and the capacity of transport service providers. These issues require a wide spectrum of research and analysis to determine expected future economic and social benefits from the implementation of environmentally friendly infrastructure investments and increasing capacity of service providers. The paper touches on the problem of the so-called green mobility in urban areas and the main management strategies associated with its development. A general formulation of the decision model, including boundary conditions and the criteria function using a sum of revenues from making the public transport offer more attractive, were proposed and discussed.
... The optimization of routes for environmental externalities using a GIS has been investigated by numerous authors, following the general approach of assigning eco-related values as fuel consumption and others to single road segments (Andersen, Jensen, Torp, and Yang (2013), Pamučar, Gigović, Ćirović, and Regodić (2016), Scora, Boriboonsomsin, and Barth (2015), Tavares, Zsigraiova, Semiao, and Carvalho (2009) and Zsigraiova, Semiao, and Beijoco (2013)). Such values can be derived from measurements for specific road segments of a certain area under study, data collections or by implementing EEMs. ...
... Furthermore, this approach is limited to road segments within study areas with collected data, not distinguishing between different vehicle types and neglecting the effects of road inclination. Like the approach by Andersen et al. (2013), and Pamučar et al. (2016), this study assigned weights of different influencing aspects, such as noise, different pollutants, land use, road inclination and average speed and applied a multi-criteria method of Weighted Linear Combination. The respective weights are assigned to the road segments of the road network under study to define green routes for city logistics. ...
... Nevertheless, these studies neglected the effects of road inclination and varying velocities, which have a significant impact on fuel consumption and CO 2 -Emissions. The works by Andersen et al. (2013), and Pamučar et al. (2016) are not able to estimate fuel consumption or CO 2 -Emission estimates, which is covered by the remaining publications by implementing EEMs as in Scora et al. (2015), Tavares et al. (2009) and Zsigraiova et al. (2013). Furthermore, some approaches are only applicable to particular study areas (Pamučar et al., 2016;Tavares et al., 2009;Zsigraiova et al., 2013), where extensive data collections are commercially available or have been conducted. ...
Road freight transportation accounts for a significant share of the worldwide CO2-Emissions, indicating that respective operations are not sustainable. Regarding the forecasted increase in CO2-Emissions from this sector, undertaking responsibilities for its environmental impact are needed. Although technical and strategic solutions to reduce emissions have been introduced, or are in development, these rarely yield instant emission reduction potentials. A strategic approach to reducing them instantly, based on the given infrastructure and existing vehicle fleet, may be achieved through route optimization. Route optimization is a well-researched topic in the transportation domain. However, it is mainly used to reduce transportation times and expenses. Rising expectations towards sustainability by authorities and consumers led to an increased interest in route optimization in which environmental externalities, such as fuel consumption and CO2-Emissions are minimized. This paper introduces a Geographic Information System (GIS) based 3D-Routing-Model, which incorporates models to estimate vehicle fuel consumption while taking effects, such as road inclination and varying velocities into account. The proposed model utilizes a Digital Elevation Model (DEM) to enrich a road network with elevation data. The 3D-Routing-Model is applied in different distribution scenarios within the framework of an artificial company in the Lisbon Metropolitan Area, Portugal to evaluate the effects of road inclination on vehicles fuel consumption and its proportional CO2-Emissions. Results indicate that eco-friendly routes can yield significant fuel and emission saving potentials of up to 20% in the tested scenarios. However, eco-friendly routes are characterized by longer distances as well as operation times, which leads to increased expenses. The question remains if companies within the transportation sector are more interested in maximizing their profits, or investing in a sustainable future.
... Geographic information system (GIS) has been used for achieving green transport involving network analysis by processing spatial data and creating vehicle routes (Pamu et al., 2016). GIS is a framework for integrating many types of data to analyze spatial information in a visual format using maps. ...
... Routing Green Vehicles consider a small number of parameters. It could be used to reduce the energy requirements of vehicle routing, minimize energy and weighted load, optimize the travel distance and load impacts on fuel costs, or define the logistics costs and environmental parameters (Pamu et al., 2016). Abousaeidi et al. (2016) adopted GIS modeling using network analyst to determine the quickest routes for fresh vegetable delivery which enabled to prevent the perishing and reducing the transportation costs. ...
This paper evaluated the carbon footprint of the papaya supply chain to Yasothon Market in Yasothon province, Thailand. There is high consumption of papaya in Yasothon municipality but a lack of papaya plantations in the area lead to a vast amount import of papaya. The study developed a green supply chain and logistics model, using network analysis. The best route for each significant case was the shortest route of the total distance from each registered stop. The results of the analysis revealed that papaya distributed from Ubon Ratchathani and Sisaket Farms should use the route generated by driving and distance impedance with the lowest greenhouse gas emissions at 898.42 kg CO 2 eq./FU. Meanwhile, the distribution from Nakorn Ratchasima should use the driving distance impedance to generate the route with the lowest greenhouse gas emissions at 987.37 k kg CO 2 eq./FU. While the papaya supply chain from Kamphaeng Phet, Kanchanaburi, Lopburi, and Ratchaburi to Khon Kaen Market with driving distance impedance is the best solution among all the alternative routes as it generates the lowest greenhouse gas emissions at 6620.23 kg CO 2 eq./FU. The results suggest that the distribution center can help reducing the distance, resulting in reducing greenhouse gas emissions. The results of the study can suggest the sustainable index of the papaya supply chain by comparing the conventional and improved environmental impact of the papaya supply chain from the green logistics model. The alternatives will be the suggestion of pathways towards improvements in green supply chain and logistics of papaya, which can also be considered for implementation in other agricultural products.
... From a methodological point of view, the defined landslide susceptibility areas in the western part of the Republic of Serbia include the following main steps ( Figure 2). The primary advantages of the BW method for the landslide susceptibility mapping [57][58][59] suggested by the authors are as follows: (1) compared with the analytic hierarchy process (AHP) method, which is most commonly used in the literature to determine weight coefficients [60], it requires significantly fewer pairwise comparisons (the AHP method requires n(n−1)/2 comparisons, the BW 2n−3 comparisons); (2) the values of the weight coefficients obtained by the BW method are more reliable because comparison in the BW method is carried out with a higher consistency ratio compared with the AHP method; (3) while for the majority of MCDM models (e.g., the AHP) the consistency ratio is a test of whether the criteria comparison is consistent or not, in the BW method the consistency ratio is used to determine the level of confidence since the BW outputs are always consistent; (4) the BW model only uses integers for the criteria pairwise comparison, as opposed to the other MCDM methods (e.g., the AHP), which also require the use of fractional numbers [61]. ...
... Since the method is of a very recent date, the literature has, so far, only contained the traditional (crisp) BW method [57][58][59]62] and the modification of the BW method performed by using fuzzy numbers [63]. The following section presents the algorithm for the BW method that includes the following steps: The primary advantages of the BW method for the landslide susceptibility mapping [57][58][59] suggested by the authors are as follows: (1) compared with the analytic hierarchy process (AHP) method, which is most commonly used in the literature to determine weight coefficients [60], it requires significantly fewer pairwise comparisons (the AHP method requires n(n−1)/2 comparisons, the BW 2n−3 comparisons); (2) the values of the weight coefficients obtained by the BW method are more reliable because comparison in the BW method is carried out with a higher consistency ratio compared with the AHP method; (3) while for the majority of MCDM models (e.g., the AHP) the consistency ratio is a test of whether the criteria comparison is consistent or not, in the BW method the consistency ratio is used to determine the level of confidence since the BW outputs are always consistent; (4) the BW model only uses integers for the criteria pairwise comparison, as opposed to the other MCDM methods (e.g., the AHP), which also require the use of fractional numbers [61]. ...
The main goal of this article is to produce a landslide susceptibility map by using the hybrid Geographical Information System (GIS) spatial multi-criteria decision analysis best-worst methodology (MCDA-BWM) in the western part of the Republic of Serbia. Initially, a landslide inventory map was prepared using the National Landslide Database, aerial photographs, and also by carrying out field surveys. A total of 1082 landslide locations were detected. This methodology considers the fifteen conditioning factors that are relevant to landslide susceptibility mapping: the elevation, slope, aspect, distance to the road network, distance to the river, distance to faults, lithology, the Normalized Difference Vegetation Index (NDVI), the Topographic Wetness Index (TWI), the Stream Power Index (SPI), the Sediment Transport Index (STI), annual rainfall, the distance to urban areas, and the land use/cover. The expert evaluation takes into account the nature and severity of the observed criteria, and it was tested by using two scenarios: the different aggregation methods of the BWM. The prediction performances of the generated maps were checked by the receiver operating characteristics (ROCs). The validation results confirmed that the areas under the ROC curve for the weighted linear combination (WLC) and the ordered weighted averaging (OWA) aggregation methods of the MCDA-BWM have a very high accuracy. The results of the landslide susceptibility assessment obtained by applying the proposed best-worst method were the first step in the development of landslide risk management and they are expected to be used by local governments for effective management planning purposes.
... Since this work does not rely on a fuel consumption model, it is very accurate for the paths and vehicles for which fuel consumption data is available, but it does not transfer to other settings without the collection of a large amount of data in that setting. Pamucar et al. (2016) utilize a similar approach and include other negative externalities associated with transportation, such as noise, land use, and pollutants other than CO 2 . Schröder and Cabral (2019) consider a Digital Elevation Model and Copert III emissions model to compute the greenest path. ...
We study the effect of using high-resolution elevation data on the selection of the most fuel-efficient (greenest) path for different trucks in various urban environments. We adapt a variant of the Comprehensive Modal Emission Model (CMEM) to show that the optimal speed and the greenest path are slope dependent (dynamic). When there are no elevation changes in a road network, the most fuel-efficient path is the shortest path with a constant (static) optimal speed throughout. However, if the network is not flat, then the shortest path is not necessarily the greenest path, and the optimal driving speed is dynamic. We prove that the greenest path converges to an asymptotic greenest path as the payload approaches infinity and that this limiting path is attained for a finite load. In a set of extensive numerical experiments, we benchmark the emissions reduction of our dynamic speed and the greenest path policies against policies that ignore elevation data. We use the geo-spatial data of 25 major cities across 6 continents. We observe numerically that the greenest path quickly diverges from the shortest path and attains the asymptotic greenest path even for moderate payloads. Based on an analysis of variance, the main determinants of the emissions reduction potential are the variation of the road gradients along the shortest path as well as the relative elevation of the source from the target. Using speed data estimates for rush hour in New York City, we test emissions reduction by comparing the greenest paths with optimized speeds against the fastest paths with traffic speed. We observe that selecting the greenest paths instead of the fastest paths can significantly reduce emissions. Additionally, our results show that while speed optimization on uphill arcs can significantly help reduction, the potential to leverage gravity for acceleration on downhill arcs is limited due to traffic congestion.
... Main components of GIS are hardware, software, data, people and applications/methods. GIS methods can be used in the variety of fieldsfrom geography, geology, hydrology, geomorphology, to demography, economics, urban planning, geodesy and civil engineering (Zhou, 2021). GIS can also be used in the domain of logistics to optimize routes and significantly reduce the cost of distribution (Chen et al., 2021), make evaluation of logistics performance (Özceyan et al., 2016), plan routes for green vehicles and decrease air pollution (Pamučar et al., 2016) and many more areas of logistics. ...
With the development of new technologies, industrial processes are nowadays changing rapidly. The essence of logistics has remained unchanged – to enable the most efficient flow of goods between the two parties. However, with changes in individual needs, it is now necessary to use new tools in order to be effective at a satisfactory level. As a system for collecting, storing, analyzing and visualizing spatial data, Geographic Information System (GIS) comes to the fore here. The aim of this paper is to show how GIS and GIS experts fit into the framework of smart logistics and what would be the path for further development of GIS application in logistics.
... At the modelling stage, optimization strategies, by abstracting complicated real-world problems into network models using GIS, are commonly utilized to formularize the transportation problem into research targets, decision variables, and constraints (Delmelle et al., 2012). Typical optimizing targets in transportation include minimizing relevant costs (Pamučar et al., 2016), guaranteeing reasonable network flow (Lim and Lee, 2013), and maximizing transport accessibility (Tahmasbi and Haghshenas, 2019). Correspondingly, several common constraints cover transport infrastructure physical capacity, general road network properties (Brachman and Dragicevic, 2014), and features of detailed transport planning activities (Saeheaw and Charoenchai, 2017). ...
Transportation is a key component in urban design for cities’ efficiency and residents’ life quality, and GIS has the capability of handling data management, model design, and scientific decision-making for transportation studies. This article reviews how spatial big data and analysis strategies help GIS-T studies from the phases of conceptual design, modelling, and decision-making. In this research, we firstly summarized categorizes of data objects and relevant information for real-world issues from transportation applications in the conceptual design phase. In the modelling phase, optimization strategies for transport planning and accessibility measures through network data were also summarized. Finally, we reviewed spatial analysis methods in supporting transport decision-making, and how spatial methods take advantage of geography features of transport variables in previous studies. Our research primarily focuses on geography research with transportation topics as applications, and this work can help transport experts to have a better understanding of GIS values for transportation modelling and planning.
... Dyczkowska and Reshetnikova [15] analyzed logistics centers in Ukraine, with a special focus on those in the city of Lviv. Pamučar et al. [16] investigated transport route optimization between urban logistics centers to reduce environmental impact and harmful gas emissions. ...
In urban logistics, the strategic placement of logistics centers significantly influences cost efficiency. This study explores optimal locations for establishing logistics centers within the Brcko District of Bosnia and Herzegovina. The methodology involves expert evaluations, employing linguistic values to assess criteria and alternatives. A fuzzy approach is utilized to translate these values into actionable data. The application of the fuzzy Logarithm Methodology of Additive Weights (LMAW) method was instrumental in ascertaining the significance of various location selection criteria. Amongst these, connectivity to multinodular transport emerged as paramount.
Concurrently, the fuzzy Combined Compromise Solution (CoCoSo) method facilitated the ranking of potential sites,
identifying the Brka-Gajine Zone as the most favorable. These findings were substantiated through a comparative and
sensitivity analysis. Comparative analysis reinforced the CoCoSo method’s alignment with results derived from the
fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Sensitivity analysis revealed
fluctuations in the rankings of locations A2 and A5 across twelve scenarios. This research not only demonstrates
the efficacy of fuzzy methodologies in urban logistics center location selection but also highlights the Brka-Gajine
Zone’s potential as a burgeoning business hub, poised to become a dominant force in logistics. The study’s findings
offer valuable insights for urban planning and logistics optimization, emphasizing the role of multidimensional
assessment in such decision-making processes.
... Organizational: Involves operational decisions of transport companies or shippers, including the definition of both centralized and decentralized storage systems, development and implementation of intermodal transport [37], use of urban mobile warehouses for deliveries and pickups [55][56][57][58], micro-hubs in parking lots [59], route planning for vehicles [47,60,61], after-hours deliveries, [51,59,62,63], overnight deliveries [52,53,61,64,65], use of shared vehicles or deliveries [50,52,54,[65][66][67], supply consolidation [34,46,68], crowdsourcing [58,69], location alternatives for freight distribution centers [41,44,[70][71][72][73][74][75], and load unit standardization [74]. ...
The tension between city logistics and its impact on sustainable urban development is evident. Often, local environmental decisions overlook the effects on urban freight logistics, lacking consideration for stakeholders. To address this, utilizing multi-criteria analysis becomes relevant for informed urban planning and management decision making. In this context, this paper conducts a systematic literature review from 2012 to 2022, focused on implementing the multi-criteria analysis methodology to evaluate alternatives for solutions in urban freight logistics. The PRISMA tool was used in the review to select publications and categorize the information obtained to address the research questions. Results display the most prominent authors and publications, authors’ country affiliations, annual publication frequency, research objectives, used frameworks, involved actors, defined evaluation criteria, types of alternatives for solutions considered, and MCDM methods applied. The main finding is that the most commonly used MCDM methods were AHP hybrid followed by MAMCA. In addition, no clear correlation between the pursued objectives and the MCDM methods employed by the researchers is identified. It is important to note that all publications with the highest number of citations use fuzzy methods in their analyses.
... Since this work does not rely on a fuel consumption model, it is very accurate for the paths and vehicles for which fuel consumption data is available, but it does not transfer to other settings without the collection of a large amount of data in that setting. Pamučar et al. (2016) utilize a similar approach and include other negative externalities associated with transportation, such as such as noise, land use, and pollutants other than CO 2 . Schröder and Cabral (2019) consider a Digital Elevation Model and Copert III emissions model to compute the greenest path. ...
... Since this work does not rely on a fuel consumption model, it is very accurate for the paths and vehicles for which fuel consumption data is available, but it does not transfer to other settings without the collection of a large amount of data in that setting. Pamučar et al. (2016) utilize a similar approach and include other negative externalities associated with transportation, such as such as noise, land use, and pollutants other than CO 2 . Schröder and Cabral (2019) consider a Digital Elevation Model and Copert III emissions model to compute the greenest path. ...
We study the effect of using high-resolution elevation data on the selection of the most fuel-efficient (greenest) path for different trucks in various urban environments. We adapt a variant of the Comprehensive Modal Emission Model (CMEM) to show that the optimal speed and the greenest path are slope dependent (dynamic). When there are no elevation changes in a road network, the most fuel-efficient path is the shortest path with a constant (static) optimal speed throughout. However, if the network is not flat, then the shortest path is not necessarily the greenest path, and the optimal driving speed is dynamic. We prove that the greenest path converges to an asymptotic greenest path as the payload approaches infinity and that this limiting path is attained for a finite load. In a set of extensive numerical experiments, we benchmark the CO2 emissions reduction of our dynamic speed and the greenest path policies against policies that ignore elevation data. We use the geo-spatial data of 25 major cities across 6 continents. We observe numerically that the greenest path quickly diverges from the shortest path and attains the asymptotic greenest path even for moderate payloads. Based on an analysis of variance, the main determinants of the CO2 emissions reduction potential are the variation of the road gradients along the shortest path as well as the relative elevation of the source from the target. Using speed data estimates for rush hour in New York City, we test CO2 emissions reduction by comparing the greenest paths with optimized speeds against the fastest paths with traffic speed. We observe that selecting the greenest paths instead of the fastest paths can significantly reduce CO2 emissions. Additionally, our results show that while speed optimization on uphill arcs can significantly help CO2 reduction, the potential to leverage gravity for acceleration on downhill arcs is limited due to traffic congestion.
... Nataraj et al. [44] combined the concept of flow consolidation in the logistics center and the cooperation strategy of city logistics participants to reduce the negative effects of CL. Pamučar et al. [45] optimized the delivery of goods from the logistics center by routing eco-vehicles. Crainic and Montreuil [46] proposed the concept of the synergy of logistics centers and the Physical Internet to increase the efficiency of the delivery of goods in the city. ...
Globalization, the growth of the world population, urbanization and the growth of the volume of the flow of goods have generated numerous problems in city logistics (CL). The opportunity to solve them is found in various fields by defining and implementing initiatives, concepts, measures, modern technologies and scenarios. The efficiency of the solution largely depends on the efficiency of logistics centers, which is one of the key subsystems of CL. The requirements for the reliable delivery of goods to customers in urban areas are conditioned by the efficiency their order fulfillment in logistics centers. Therefore, optimizing material handling (MH) time and costs aimed at reducing delivery errors, minimizing damage to goods and increasing customer service efficiency is directly conditioned by the automation of MH in logistics centers. Accordingly, this paper aims to rank and select smart MH solutions in logistics centers where deliveries are prepared for the supply of the city area. This paper proposes four smart solutions for a real company, and fourteen criteria are selected for the evaluation. A new hybrid Multi-Criteria Decision-Making model that combines the Fuzzy Analytic Hierarchy Process method, used to determine the criteria weights, and the Fuzzy COmprehensive distance-Based RAnking (FCOBRA) method, used to rank the alternatives, is proposed. The application of the model shows that the best alternative is the implementation of an autonomous forklift, which can greatly automate logistics activities and reduce the rate of delivery errors. The main contributions of this research are the definition of smart solutions, a framework for their evaluation and a new model for their ranking.
... Macharis et al. (2014) evalúan la interconexión de transporte de ferrocarril y carretera que permita mejorar la logística de última milla, incluyendo tres metodologías: el análisis costo-beneficio social, el modelo de negocio y análisis multicriterio multiactor. Pamučar et al. (2016) buscan la optimización de rutas verdes para centros logísticos de las ciudades, integrando el método multicriterio de combinación lineal ponderada (WLC) y el algoritmo de Dijkstra de programación lineal. ...
The paper presents a protocol for conducting a systematic literature review (SLR) on the application of multicriteria decision analysis methods (MCDM) as a tool for evaluating urban freight logistics. The paper presents a protocol for conducting a systematic literature review (SLR) on the application of multicriteria decision analysis methods (MCDM) as a tool for evaluating urban freight logistics.This research topic arises from the growing interest of public and private actors in achieving objectives of reducing environmental and social impacts and/or improving operational efficiency in city logistics.The search is focused on publications comprised in the period between 2012 and 2020. Finally, with the selected works, a descriptive analysis is carried out, which allows obtaining a preliminary result of the RSL that will be developed in future research.SDGs' supported by research: SDG08 Decent Work and Economic Growth and SDG11 Sustainable Cities and Communities.
... Overall, the parameters are from the areas of environment, health, space use and logistics operating costs [85]. These parameters are particularly relevant for planning in urban areas with vehicles with alternative vehicles [86][87][88]. By taking these parameters into account, the modelling can have a positive influence on the environment by avoiding harmful gas emissions [89,90]. ...
This paper provides a systematic and up-to-date review and classification of 87 studies on green last-mile business for sustainable management. In particular, the most important study areas and results are highlighted and an outlook on future research opportunities in the field of sustainable stock management is given. Sustainability in logistics depends on many factors, and elementary differences in the orientation of the logistics sector can bring further challenges. This is shown by the number of published papers. This paper examines the literature that does not focus on courier, express or parcel delivery (CEP). For this purpose, a systematic literature search was conducted on the topic of sustainability in the last-mile business. Publications for the period from 2014 to 2021 were identified as significant. It becomes clear that the logistics industry must further differentiate itself to be able to act in a future-oriented manner. The effects of the logistics industry and the technologies used in it have far-reaching consequences for social coexistence and should therefore be included. Challenges lie not only with logistics companies, but also with consumers and government authorities. In the paper it becomes clear that the logistics concept of the last mile is applied in all forms, but the research area of one-person delivery or two-person delivery is on a different level. Here, the concept of two-person delivery will be pursued further, as it functions similarly to a CEP service provider, but the framework conditions differ greatly. The two-person loading system makes it possible to transport large and bulky goods such as furniture without the risk of damage during delivery. Furthermore, the specifics of sustainable management of the last mile as well as the limits of the topic are discussed. This should stimulate future research.
... Operational parameters of speed, combustion, tonnage, and exhaust emissions translate into the quality of ecology. These topics are addressed in the research of Pamučar D. The TSDSM system [13] integrates multi-criteria weighted linear combination methods of WLC and GIS (spatial data). Using the developed model, it is possible to determine routes in the ecological aspect and maximize environmental impact. ...
... In addition, software such as ArcGIS ® has a database of road conditions and historic traffic information which improve the results for travel time and route selection. Applications of GIS in the VRP freight literature include freight system analysis [32], forest firefighting [33], waste collection routes [34][35][36][37] (the latter also including Artificial Neural Network (ANN)), truck configuration [34], emissions including carbon dioxide [38,39], and operation costs [40]. ...
Urban pickup and delivery (PUD) activities are important for logistics operations. Real operations for general freight involve a high degree of complexity due to daily variability. Discrete-event simulation (DES) is a method that can mimic real operations and include stochastic parameters. However, realistic vehicle routing is difficult to build in DES models. The objective is to create a DES model for realistic freight routing, which considers the driver’s routing decisions. Realistic models need to predict the delivery route (including time and distance) for variable consignment address and backhaul pickup. Geographic information systems (GIS) and DES were combined to develop freight PUD models. GIS was used to process geographical data. Two DES models were developed and compared. The first was a simple suburb model, and the second an intersection-based model. Real industrial data were applied including one-year consignment data and global positioning system (GPS) data. A case study of one delivery tour is shown, with results validated with actual GPS data. The DES results were also compared with conventional GIS models. The result shows the intersection-based model is adequate to mimic actual PUD routing. This work provides a method for combining GIS and DES to build freight operation models for urban PUD. This has the potential to help industry logistics practitioners better understand their current operations and experiment with different scenarios.
... Their limited case study must not undermine the importance of their proposed criteria, which can be examined in other historic cities with similar transportation problems. This piece of work came to complement the extensive research study of Ref. [54] in which the authors proposed a transport spatial decision support model to optimise the implementation of environmentally friendly vehicles in an existing road network using several parameters, such as environmental pollution, health, use of space and logistics operating costs. ...
To date, the knowledge regarding the potential uses of Geographic Information Systems (GIS) in Supply Chain Management (SCM) and how the GIS applications can deliver business benefits is limited. To explore the current uses of GIS in SCM, a systematic literature review (SLR) was conducted. Three databases (Web of Science, ProQuest and Business Source Premier) were explored, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. A total of 79 papers were included in the literature review. The combined findings showed that the GIS applications in SCM were a) network/ transportation analysis/ routing algorithms (53 papers), b) Location-Allocation Site Search/ Selection (using multiple-criteria decision analysis [MCDA]) (45 papers), c) spatial analysis (people or land) (34 papers), d) connection with optimisation tools (32 papers) and e) visualisation/ monitoring or Building Information Modelling (BIM) (8 papers). The industries and related Supply Chain (SC) domains that used GIS were a) Biomass Biofuel/Wood (33), b) Logistics (22), c) Humanitarian/ Emergency/ Healthcare (10), d) Food/ Agro-Industry (5), e) Petroleum/ Coal/ Shale Gas (3), f) Faecal Sludge (2), g) Recycle & product footprint (2) and h) Construction (2). The research case studies took place in 26 countries, and the most prominent GIS software provider was Esri's ArcGIS. The findings of the first literature review of the GIS applications in SCM showed that many business industries have not utilised the GIS capabilities, such as visualisation, spatial analysis, optimisation, and site research. However, GIS can significantly contribute to SCM decision making by providing answers to cost minimisation, supplier selection, facility location, SC network configuration and asset management.
... A similar approach was used by Ozceylan et al. (2016) to evaluate potential locations for FVs using a GIS-based MCA method. Pamucar et al. (2016) considered the integration of the multi-criteria method, which involved the weighted linear combination and the modified Dijkstra algorithm within a GIS to optimise green routes for the city logistics centre. ...
... A similar approach was used by Ozceylan et al. (2016) to evaluate potential locations for FVs using a GIS-based MCA method. Pamucar et al. (2016) considered the integration of the multi-criteria method, which involved the weighted linear combination and the modified Dijkstra algorithm within a GIS to optimise green routes for the city logistics centre. ...
... In various studies, such factors as speed [15], the weighted load [16], traffic load on the route and their complex influence on different objective functions (apart from such usual ones as logistics operating costs and transportation time): either fuel consumption [17], total CO 2 emissions [18], or their combinations [19] were considered. The paper [20] provides decision support methodology that unites network science, green logistics and transportation accessibility research. A detailed presentation and description of studies that consider the problem of "green" vehicles routing can be found in the research of [21]. ...
The article describes the ways of industrial development in the era of transition from a linear model of the economy to a circular model, as well as new trends in the development of logistics. It shows the interconnection of processes in production systems, logistics and services, their role in ensuring sustainable green growth. It is shown that by closing the loop of product lifecycles, reverse logistics plays an important role to transitioning to a circular economy. The article presents an example of planning the supply of spare parts when organizing services in foreign markets. Planning is based on multidimensional analysis of failure and modeling data. For this purpose, an information system was developed. The found failure probabilities of units and parts were used to build a model of the reverse logistic chain, within which the parameters of the formation of a reverse flow, differentiated for various operating conditions and vehicle subsystems, were introduced for the first time.
... Their case study shows that the most environmentally friendly solution could reduce fuel consumption of trucks by 2.5% on average while increase costs by 10.8%. Pamučar et al. (2016) design a spatial decision support model for carrying out the optimization of green routes for consolidation centers under the objective function of environment, health, and logistics operating costs. Heni et al. (2019) on the other hand investigate the cost-emission relationship considering the rerouting of trucks around congestion areas. ...
Road freight transportation literature increasingly concentrates on environmental aspects to reduce logistics contribution to carbon dioxide emissions. Some literature reviews highlight specific mitigation and adaptation strategies, but the overarching research directions to identify emerging areas and general trends of the field have not yet been clustered or synthesized. This paper presents a systematic quantitative review of the road freight transportation decarbonization literature leveraging bibliographic coupling and network analysis techniques. It contributes to the understanding of road freight decarbonization and provides recommendations for further investigations of the field by systematically mapping the literature body. This way, key research clusters are outlined and visualized to understand the underlying knowledge structure. The findings reveal a diverse and fast-growing research field, which in large parts focuses on route optimizations, last-mile solutions, and alternative fuels, while offering future research opportunities that address organizational barriers currently hindering collaboration and technological or operational measures for long- haul transportations.
... Approaches that include decision support concentrate on VRP and LRP applications but mostly lack aspects of sustainability or emission reduction (Gayialis and Tatsiopoulos 2004;Li et al. 2007;Lin et al. 2014;Ruiz et al. 2004;Santos et al. 2011), which results in an inadequate usability of green city logistics research in practical applications. As an improvement, Pamučar et al. (2016b) present a DSS for the optimization of green routes for urban logistics centers with a transport spatial decision support model considering environmental externalities. Their paper appears to be most relevant to our proposed approach, but it neglects the integration of a sustainable fleet composition. ...
The worldwide trend of urbanization, the rising needs of individuals, and the continuous growth of e-commerce lead to increasing urban delivery activities, which are a substantial driver of traffic and pollution in cities. Due to rising public pressure, emission-reducing measures are increasingly likely to be introduced. Such measures can cover diesel bans or even entire car-free zones, causing drastic effects on delivery networks in urban areas. As an option to reduce the risk of a regulation-induced shock, we present a resilience-oriented network and fleet optimization. We propose an innovative parcel delivery concept for last mile delivery (LMD) operations and develop an optimization model to support tactical planning decisions. Our model minimizes overall operating costs by determining optimal locations for micro depots and it allocates transport vehicles to them. An adjustable CO2-threshold and external costs are included to consider potential regulatory restrictions by city authorities. We implement our model into a decision support system (DSS) that allows analyzing and comparing different scenarios. We provide a computational study by evaluating and discussing our DSS with an example of a mid-sized German city. Our results and findings demonstrate the trade-off between cost and emission minimization by quantifying the impacts of various fleet compositions. The proposed logistics concept represents an option to achieve environmentally friendly, cost-efficient, and resilient LMD of parcels.
... Link-based indicators can be applied into advanced traffic management systems as vehicle routing problems, but existing literature around this topic is mostly focused on the use of empirical models for route choice optimization in urban areas (Ćirović et al., 2014;Jovanović et al., 2014;Pamučar et al., 2016a;Pamucar and Goran Ćirović, 2018;Pamučar et al., 2016b). ...
... In various studies, such factors as speed [9], the weighted load [10], traffic load on the route and their complex influence on different objective functions (apart from such usual ones as logistics operating costs and transportation time): either fuel consumption [11], total CO 2 emissions [12], or their combinations [13], were considered. Paper [14] provides decision support methodology that unites network science, green logistics and transportation accessibility research. When planning spare parts delivery reasonable transportation mode selection is the priority task. ...
... Other recent studies propose decision-making spatial analysis models in which GIS and fuzzy systems are applied in engineering optimization analysis to solve decision-making problems, such as selection of the best logistic locations [7], the study of the prevention of a stroke [8], the optimization of green routes for city logistics centers [9], and the selection of the most suitable sites for wind-farm installments [10]. ...
Here, we present a new unsupervised method aimed at obtaining a partition of a complex urban system in homogenous urban areas, called urban contexts. Our model integrates spatial analysis processes and a fuzzy rule-based system applied to manage the knowledge of domain experts; it is implemented using a GIS platform. The area of study is initially partitioned in microzones, homogeneous portions of the urban system, which are the atomic reference elements for the census data. With the contribution of domain experts, we identify the physical, morphological, environmental, and socio-economic indicators needed to identify synthetic characteristics of urban contexts and create the fuzzy rule set necessary for determining the type of urban context. We implement the set of spatial analysis processes required to calculate the indicators for the microzones and apply a Mamdani fuzzy rule system to classify the microzones. Finally, the partition of the area of study in urban contexts is obtained by dissolving continuous microzones belonging to the same type of urban context. Tests are performed on the Municipality of Pozzuoli (Naples, Italy); the reliability of the out model is measured by comparing the results with the ones obtained through a detailed analysis.
... Las externalidades son un componente importante que en distintos casos corresponde a un efecto de una conducta negativa o simplemente una acción natural de la movilidad. Las externalidades en el transporte corresponden a una serie de acciones que afectan la operación y el nivel de servicio, según el modo de desplazamiento (Kairuz, 2014;Pamučar, Gigović, Ćirović, & Regodić, 2016;Schliwa, Armitage, Aziz, Evans, & Rhoades, 2015). ...
RESUMEN Con esta investigación se pretende determinar el impacto sobre el transporte público que genera la mala organización y el uso de la sección vial por parte de los operadores de servicios logísticos y reparto en la ciudad en horas donde la demanda por la infraestructura vial debe ser priorizada para otros usuarios. Para esto, por medio de la micro simulación de información de tráfico en vissim, se caracterizarán las problemáticas observadas en sectores con usos de suelo mixto correspondiente zonas comerciales. Teniendo en cuenta variables de tiempo de desplazamientos, consumo de combustibles y emisión de gases en uno de los corredores viales más concurridos en la ciudad de Bogotá. Mediante el estudio de datos abiertos, complementados con información tomada en campo se logra el análisis de los parámetros antes mencionados sobre la infraestructura vial, los cuales corresponden a un corredor que se usa como vía intermedia en la ciudad, por la cual operan rutas de transporte público, una demanda importante de camiones de reparto pequeños, además del flujo normal de usuarios de autos y motos que corren la ciudad de norte a sur (un solo sentido de operación). 1. INTRODUCCIÓN La calle como unidad urbana, está compuesta por espacios para la interacción entre los habitantes de un lugar común, el espacio urbano cuenta con características únicas que se derivan de los usos del suelo. A nivel urbano y de ciudad existen sectores donde las calles están dedicadas al tránsito de tramos con usos de suelo mixto, aquí es posible encontrar todo tipo de servicios sobre un único corredor vial, estos sitios por lo general integran servicios públicos, comerciales, habitacionales, educativos y recreativos convirtiéndolos en atractores y distribuidores de una buena parte de viajes en la ciudad. A nivel general, se han caracterizado tres tipos de usuarios en los distintos corredores comerciales de la ciudad. Quienes realizan actividades de reparto o logística, usuarios y operadores de transporte público y los residentes o trabajadores del sector. Partiendo de la información de datos abiertos y la toma de información en campos, en este artículo se verifican los efectos derivados de la mala distribución del espacio público y un escaso
... ptimisation are the second theme identified. Escuín et al. (2012) compared a traditional distribution system with and without a UCC with a vehicle routing model, analysing distance travelled and travel time. Travel distance, together with factors such as number of trips, was also a central parameter in Cattaruzza et al. (2016)'s optimisation model.Pamučar et al. (2016) used parameters such as environment, health, use of space and logistics cost.Li et al. (2016) also addressed the environmental aspect by striving to minimise CO 2 emissions per ton-kilometre. ...
Purpose
Urban consolidation centre (UCC) is a popular initiative targeting the challenge of negative environmental and social impacts from freight transports in cities. Despite this, UCC often fails in practice, which indicates a knowledge gap. Furthermore, research within the field can be described as fragmented, transdisciplinary and fast growing. The purpose of this paper is to provide an overview of the field by describing dominant categories and themes within the area, identify gaps in order to propose a future research agenda, and provide insights into the needs of practitioners.
Design/methodology/approach
A systematic literature review (SLR) targeting journal articles based on UCCs has been constructed with a supplementary snowball approach. A content analysis was performed to categorise themes in the research on UCCs and to identify research gaps, both within and outside the categories identified.
Findings
Despite substantial research on UCC, very little research ends up in academic journals. In all, 56 articles address UCC. The most common topics were the role of stakeholders, design of distribution structures and transport resources, environmental and social consideration, and economic considerations. Much focus is directed towards finding “optimal” solutions and designs for potential initiatives with very little, if any, consideration to financial viability or the management of the UCC initiative.
Research limitations/implications
This research points out existing gaps in the literature and proposes a future research agenda with UCCs as the focus. For example, although environmental and social arguments are often applied to justify the implementation of UCCs, few studies measure or evaluate their impact. Another important research gap is the economical consideration, both how to generate revenue and how to consider economies of scale.
Practical implications
The practical contribution of most studies is directed towards municipalities. Few findings are presented in a way to support companies. Additionally, by bridging the gaps related to how stakeholders can collaborate and describe what is happening in a UCC, practitioners can use such information as guidelines.
Originality/value
The results provide a research agenda for the fragmented research targeting UCCs, supporting the viability of future initiatives.
... The most up to date approaches to modeling and solving VAP involve: stakeholders' analysis leading to multiple objective formulations of the problem (Ćirović et al., 2014), analysis of uncertainty and imprecision of data (Pamučar et al., 2016a;Shi et al., 2015) and the application of artificial intelligence methods in the problem solving procedures (Maalouf et al., 2014;Pamučar & Ćirović, 2015;Ćirović et al., 2014). Ćirović and Pamučar (2013) claim that multiple criteria formulations of different categories of transportation decision problems are more realistic than their single criterion equivalents. ...
A useful routing system should have the capability of supporting the driver effectively in deciding on an optimum route to his preference. This paper describes the problem of choice of road route under conditions of uncertainty which drivers are faced with as they carry out their task of transportation. The choice of road route depends on the needs stated in the transport requirements, the location of the users and the conditions under which the transport task is performed. The route guidance system developed in this paper is an Adaptive Neuro Fuzzy Inference Guidance System (ANFIGS) that provides instructions to drivers based upon "optimum" route solutions. A dynamic route guidance (DRG) system routes drivers using the current traffic conditions. ANFIGS can provide actual routing advice to the driver in light of the real-time traffic conditions. In the DRG system for the choice of road route, the experiential knowledge of drivers and dispatchers is accumulated in a neuro-fuzzy network which has the capability of generalizing a solution. The adaptive neuro-fuzzy network is trained to select an optimal road route on the basis of standard and additional criteria. As a result of the research, it is shown that the suggested adaptable fuzzy system, which has the ability to learn, has the capability of imitating the decision making process of the drivers and dispatchers and of showing a level of competence which is comparable with the level of their competence.
... When defining customers for a UCC, receivers are commonly mentioned among the customer base (e.g., Gonzalez-Feliu, Malhéné, Morganti, & Morana, 2014;Lin et al., 2014;Pamučar, Gigović, Ćirović, & Regodić, 2016). Yet, all stakeholders that benefit from a UCC can be conceived as customers. ...
Although urban consolidation centres (UCC) worldwide have improved urban freight distribution and reduced externalities, other UCC initiatives have not materialised due to problems such as for example, business model limitations. All the same, researchers have rarely described business model components relevant to city logistics. In response, the purpose of this article is to analyse critical factors for viable business models of city logistics initiatives involving UCCs. Following an extensive literature review and multiple-case study of five initiatives with UCCs, we identified seven critical factors of viable city logistics business models: the ability to scale up and down the UCC solution; an ability to continuously develop and adapt to a dynamic environment; the important entrepreneurial role of the initiator as well; the acknowledgment of society; ability to innovate new services; logistics and supply chain management competence; and the ability to take full advantage of advanced IT. All seven factors describe continuously redeveloped business models seeking to seize new and unexpected opportunities, yet also indicate that city logistics systems require local authorities and municipalities to act as initiators, enablers, and customers. The models also underscore differences between purely commercial and purely municipal city logistics initiatives.
... The proposed algorithm is examined on demanding scenarios in the city of San Francisco. (Pamučar et al., 2016) proposed a transport model for routing light delivery vehicles to determine which routes should be taken by delivery vehicles in urban zones, with the aim of minimizing the costs for logistics operators, minimizing adverse environmental effects, and minimizing the social, residential, recreational parameters. A new generation of systems is developed based on multi-criteria analysis, GIS technology and algorithms for routing vehicles. ...
Vehicle routing problem is a crucial issue in which it is important to consider environmental initiatives. This issue imposes considerable environmental costs, covering a wide range of different damages on human health. However, research works that consider vehicle routing problem and environmental issue in real case studies are rather limited until now. This paper proposes a new case study approach for resolving this problem taking into account environmental criteria. Thus, the main purpose is to validate the proposed approach and help the central pharmacy of Sfax hospital in Tunisia.to optimize the distribution of pharmaceuticals products by applying an environmental model for (DARP).
As cities continue to grow, there is a pressing need to enhance the quality of life for citizens while also tackling challenges such as the rising demand for urban freight deliveries and environmental sustainability goals. However, the competition between people and goods for limited space in urban areas creates pressure on local authorities and piques the interest of consultants and researchers. This study examines how sustainability is tackled when decisionmakers and stakeholders assess alternative solutions with multi-criteria methods in different urban logistics contexts. A multi-step systematic review has been performed to examine the use of multi-criteria analysis in the specific multidisciplinary sector of urban freight logistics and how sustainability is defined and pursued by identifying 56 papers published between 2011 and 2023addressing problems related to sustainable urban logistics solutions. Despite the growing number of applications and scientific publications, a standard methodological framework is lacking in selecting methods and criteria to evaluate sustainable logistics solutions. To fill this gap, this paper aims to map the problems addressed and the methods applied, the stakeholders involved as actors, their objectives, and the criteria chosen to support their choices. This paper investigates the decision-making process, actors and sources, and which criteria are chosen when the intent is to pursue sustainable solutions. Future research could delve deeper into the weighting process among criteria to elucidate the coherence between stated goals and actual decisions. Such research could offer valuable insights into how decisions are made and help identify areas for improvement.
Lojistik faaliyetlerin gün geçtikçe daha da yoğunlaşması ile artan enerji tüketimi ve sera gazı emisyonları çevresel sürdürülebilirliğe yönelik kaygılar yaratmakta ve taşımacılıkta farklı amaçlar edinmeyi zorunlu hale getirmektedir. Böylece, rotalama problemlerinde maliyet, mesafe ve zaman gibi temel amaçların yanı sıra yakıt tüketimi veya emisyonların da gözetilmesi kritik hale gelmektedir. Yakıt tüketimini etkileyen önemli unsurlardan biri olan yol eğiminin göz ardı edilmesi veya yüzeysel olarak hesaba katılması gerçeklikten uzak sonuçlar doğurmaktadır. Bu bağlamda, çalışmada yakıt tüketimini en aza indirmek amacıyla ele alınan Yeşil İki-Aşamalı Araç Rotalama Problemi (Y-2A-ARP)’nde, gerçekçi ve detaylı yol eğimleri ile hesaplamalar yapılmıştır. Çok kısa bir mesafede dahi eğimin oldukça değişebileceği gerçeği ile dağıtım ağında yer alan tüm yollar belirli uzunluklarda parçalara ayrılmış, her bir parçanın eğim değeri ayrı ayrı hesaplanmış ve yakıt tüketimi hesaplaması da bu ilgili değerler kullanılarak yapılmıştır. Türkiye’de bir ecza deposunun dağıtım ağının örnek alındığı çalışmada konunun uygulanabilirliği gösterilmiştir. Ayrıca, eğim ve hız değerlerindeki değişimin araçların toplam yakıt tüketimini nasıl etkileyeceğinin irdelenmesi amacıyla duyarlılık analizleri gerçekleştirilmiştir. Sonuçlar, yol eğimi ve hız faktörlerinin araçların yakıt tüketiminde oldukça etkili olduğunu ve göz ardı edilmemesi gerektiğini göstermektedir.
In the past few years, shared bicycles have become a major form of green transport. There are two types of shared bicycle systems: pile-based and pile-less. These two types of systems have different carbon emission profiles when it comes to manufacture, operation and maintenance, and disposal. This research explicates these trade-offs through a thorough life cycle assessment of Capital Bikes' shared bikes in Washington D.C., USA. Our research indicates that while the installation of platforms and docks is the primary source of carbon emissions for dockless bikes, fleet management and maintenance are the primary sources of emissions for these vehicles. This is significant because the literature has shown that both dockless bikes and piling systems boost the resilience of transportation networks during pandemics or transport outages, albeit in different ways, when consumers may choose to utilize dockless bikes for exercise or to avoid using public transport. Planners should encourage proactive maintenance and fleet management to boost environmental advantages, as manufacturing operations generate five times as much carbon emissions as disposal activities. This study contrasted the Total Normal Environmental Impact (TNEI) of a dockless system with that of a piling system in our case study. The manufacturing process of a shared bicycle produces the largest amount of carbon emissions. The carbon dioxide emissions saved by a bicycle are about 0.07 kg per day. We also demonstrate that a net decrease in emissions in the Capital Bikes case study requires that each bike be utilized for a minimum of 591 days. In order to guarantee that the carbon emissions produced by shared bicycles are optimised, travelers should be incentivized to ride for longer and firms should strive to extend the usable life of their equipment.
Logistical activities have a significant global environmental impact, necessitating the adoption of green logistics practices to mitigate environmental effects. The COVID-19 pandemic has further emphasized the urgency to address the environmental crisis. Operations research provides a means to balance environmental concerns and costs, thereby enhancing the management of logistical activities. This paper presents a comprehensive review of studies integrating operations research into green logistics. A systematic search was conducted in the Web of Science Core Collection database, covering papers published until June 3, 2023. Six keywords (green logistics OR sustainable logistics OR cleaner logistics OR green transportation OR sustainable transportation OR cleaner transportation) were used to identify relevant papers. The reviewed studies were categorized into five main research directions: Green waste logistics, the impact of costs on green logistics, the green routing problem, green transport network design, and emerging challenges in green logistics. The review concludes by outlining suggestions for further research that combines green logistics and operations research, with particular emphasis on investigating the long-term effects of the pandemic on this field.
Increasing sustainability is one of the core objectives of future supply chain networks. However, the ambitious economic, ecological, and social goals can only be achieved through novel technological frameworks accompanied by disruptive organizational change. The five essays of this dissertation investigate the adoption of sustainability-enhancing technologies and their underlying organizational transformations in order to reduce carbon emissions, improve economical performance, and increase social quality in logistics networks. Established methodologies in the form of case studies, managerial surveys, conceptual developments, Delphi surveys, and quantitative reviews are applied to ground this research empirically and to derive new concepts and research strategies. The results support researchers, practitioners, and politics in driving the adoption of sustainable measures and prepare organizations for future challenges. The first research paper, “Blockchain technology enabling the Physical Internet – A synergetic application framework”, studies the Physical Internet as an upcoming logistics concept that aims for a paradigm shift towards economically, environmentally, and socially sustainable logistics. The concept receives growing interest but requires transformations in infrastructure, technology, and business models, which existing literature intends to answer with centralized platform solutions. The paper demonstrates that centralized solutions do not meet the requirements to efficiently operate open logistics networks. Therefore, a decentralized solution is proposed which builds on a four-layered Blockchain-based framework. The framework describes in detail the configuration of the Blockchain and its integration into the Physical Internet. The implementation of the framework into the Ethereum environment is validated by an application use case that guides researchers for further analysis and practitioners for adoption opportunities. Thus, this scientific work not only contributes to a deeper understanding of the promising Physical Internet concept but also extends the knowledge about applying Blockchain technology in logistics and supply chain management in general. The second research paper, “The bumpy road to the adoption of the Physical Internet – Overcoming barriers from a stakeholder perspective”, empirically grounds drivers and barriers of the Physical Internet through a case study with 14 relevant stakeholders. This approach is distinctive, as the field is so far dominated by conceptual and modeling research. The case study sample consists of logistics service providers, shippers, and includes companies working on Physical Internet products and software. This way, the study holistically embraces the majority of the concepts’ relevant stakeholders. Based on technology adoption theory, insights about stakeholder intentions, organizational and technological readiness as well as enablers and hindrances of the concept are pointed out. As such, the study answers the two research questions regarding how and why relevant stakeholders might adopt the Physical Internet. Due to the expected far-reaching consequences of the concept at the firm level, the study contributes to a better understanding of how innovative concepts and technologies induce organizational transformations. This empirical study is the first, which scientifically investigates stakeholder intentions in the adoption process of the Physical Internet. The third essay, “How organizations prepare for the future: A comparative study of firm size and industry”, analyses future preparedness as a joint construct consisting of a company’s exploitation and exploration capabilities. While previous publications focused their research on large companies and single industries, this essay explicitly differentiates future preparedness strategies between large organizations and small and medium-sized companies, as well as between 12 different industries. Data from a managerial survey with 602 companies of the German economy identify firm size and industry as predictors for future preparedness strategies and implicate that the scope of future preparedness augments with firm size. Next to the managerial implications, which should motivate practitioners to engage in corporate foresight activities and to take a forward view for being prepared for environmental uncertainty, the study extends theory on the upcoming future preparedness phenomenon. The fourth paper, “Technology foresight for sustainable road freight transportation”, examines technological measures to improve the triple bottom line sustainability of road freight transportation. The speed at which the adoption of relevant sustainability technologies in transportation is currently progressing is too slow in order to sufficiently reduce carbon emissions and increase social quality in logistics networks. Hence, this study offers deeper knowledge about the adoption process by examining barriers hindering a broader market penetration. Based on these barriers, expected timeframes are derived answering the question when mass adoption of 14 technologies is expected to occur. Combined with the technologies’ impacts on sustainability, recommendations are made, on which technologies relevant stakeholders might focus on in the future. The study builds on a global Delphi survey with 116 experts from 25 different countries and in particular outlines the crucial role of politics in developing necessary regulative frameworks to drive sustainability in road freight transportation. The fifth paper, “Decarbonizing road freight transportation – A bibliometric network analysis”, extends the findings from the fourth paper by analyzing in detail the literature on environmental sustainability measures in road freight transportation. The study is the first attempt that quantitatively synthesizes the extensive multidisciplinary area of green road freight transportation. In the study, bibliographic coupling and network analysis techniques are leveraged to identify emerging areas and trends of the research field. As such, the study outlines and visualizes key research clusters to understand the underlying knowledge structures regarding strategies, methods, theories, and concepts. As a result, a detailed research agenda and explicit recommendations for decision-makers are derived.
The rapid transition to the digitalization of firms directs companies to speed up their decision-making processes and make technology-based decisions. The increasing environmental concerns and fossil-fuel scarcity force companies to employ new logistical aims, such as reducing fuel consumption and greenhouse gas emission in addition to the traditional cost minimization and profit maximization objectives. Traditional assumptions in fuel consumption calculation have been left not only to reach the objectives of the company and make consistent delivery plans but also to increase the solution quality of real-life problems. From this point of view, this study contributes to the related literature by developing a decision support model for a Travelling Salesman Problem that considers dynamic customer requests and realistic road gradients of the entire road network while calculating fuel consumption from transportation operations. The applicability of the developed model has been shown with a real-life case study in which laboratory samples have been collected and transferred from local family clinics to a central laboratory. Several objective functions are employed to demonstrate the benefits of considering realistic road gradients. The results of the numerical analyses on static and dynamic instances illustrate the benefits of respecting realistic road gradients in fuel consumption and addressing dynamic requests during delivery operations.
Bu çalışmada Türkiye’deki büyükşehirlerin 2010 ve 2019 yıllarına ait karayolu ulaşımından (bireysel seyahatler+yolcu ve yük taşımacılığı) kaynaklı sera gazı emisyon miktarları IPCC tarafından geliştirilen Tier 1 yöntemi kullanılarak hesaplanmıştır. Elde edilen sonuçlara göre 30 büyükşehirde 2010 yılında toplam sera gazı emisyon miktarı 43.403 Gg CO2 eşdeğer(e.) iken, 2019 yılında artarak 70.271 Gg CO2e. ulaşmıştır. 2010-2019 yılları arasında toplam sera gazı emisyon miktarı %61,90 oranında artış göstermiştir. Toplam sera gazı emisyon miktarında İstanbul, Ankara, İzmir, kişi başına düşen sera gazı emisyon miktarında Denizli, Mersin, Muğla, araç başına düşen sera gazı emisyon miktarında Mardin, Kocaeli, Diyarbakır, km2’ye düşen sera gazı emisyon miktarında ise İstanbul, Kocaeli, İzmir şehirleri ilk 3 sırada yer almaktadır. Hem 2010 hem de 2019 yılında İstanbul, Ankara, İzmir, Bursa, Mersin, Antalya, Konya ve Kocaeli ortalama emisyon miktarının üstünde değerlere sahiptir. Bu şehirlerde alınacak öncelikli önlemler ile ülkemizin karayolu kaynaklı emisyon miktarı önemli oranda düşürülebilecektir. Diğer taraftan Mardin, Van ve Şanlıurfa gibi doğu bölgemizdeki şehirlerde emisyon artış hızı diğer şehirlere göre çok daha yüksektir. Çalışmada büyükşehirler alternatif taşıma seçenekleri ve alt yapılara göre de karşılaştırılmış ve demiryolu hariç diğer seçeneklerin emisyon artış hızını azaltmada etkili olduğu tespit edilmiştir.
The improvement of logistics operation management for many tobacco companies highly depends on the reduction of distribution costs. In order to optimize routes, cigarettes are delivered through online real-time distribution system equipped with GIS/GPS. These network information technologies are crucial to creating and maintaining an efficient distribution system. Considering the applicability and flexibility of GIS/GPS network information system, this paper assesses the impact of its implementation on the logistics distribution cost from both overall and household levels. Specifically, DID and pseudo-DID models were adopted and monthly panel data of 14 prefecture-level branches of Hunan Tobacco Company during 2016-2019 were used for regression.We find that the implementation of GIS/GPS network information systems increased the total distribution cost. However, the average distribution cost was significantly reduced at per household level as the customer base expanded. A series of robustness and sensitivity tests supported above results. Furthermore, the implementation of GIS/GPS network information system is beneficial to service quality and employee performance. In addition, more time and logistics costs were saved when drivers chose “dynamic + fixed optimization” route model.
Widespread adoption of green vehicles in urban logistics may contribute to the alleviation of problems such as environmental pollution, global warming, and oil dependency. However, the current adoption of green vehicles in the last mile logistics is relatively low despite many actions taken by public authorities to overcome the negative externalities of distributing goods in cities. This paper presents a comprehensive literature review on studies investigating the adoption of green vehicles in urban freight transportation, paying specific attention to e-commerce. To shed light on the adoption of green vehicles in city logistics, the paper conducts a systematic review of the empirical literature on the topic. The 159 articles reviewed were classified into the following: (a) Optimization and scheduling (67 papers); (b) policy (55 papers); (c) sustainability (37 papers). Among the 159 articles, a further selection of 17 papers dealing with e-commerce, i.e., studies that highlight the most relevant aspects related to the integration of green vehicles in e-commerce urban logistics, was performed. Our findings indicate that green vehicles are competitive in urban deliveries characterized by frequent stop-and-go movements and low consolidation levels while incentives are still necessary for their adoption. The use of autonomous vehicles results the most promising and challenging solution for last-mile logistics.
This work aims to describe the development of the vehicle routing system Geo-Rota web. The theoretical framework addresses the integration of routing algorithms with geographic data, as well as implementation strategies used. We have done tests with instances found in the literature to validate the GRASP algorithm developed to solve the vehicle routing with multi-compartments problem. In order to demonstrate the effectiveness of the system, a case study was carried, out that generated improvements in the routes generated by the company, showing reduction of vehicles and distance. The conclusion reached was that the developed system optimizes the delivery schedules efficiently, contributing to increase the logistics efficiency of the companies.
The advantages of logistics centers for companies, cities, and countries have been discussed in the literature and generally mathematical model-based evaluations besides multi-criteria approaches are proposed for site selection processes. However, since mathematical modeling of multiple site selection often turns out to be NP-hard problem structure, it is not always possible to obtain an optimal solution by the solvers. For this reason, various meta-heuristic approaches have emerged to solve these complex models. In this context, the aim of this study is to propose an integrated methodology which seeks an optimum result efficiently regarding a logistics center location selection problem. Thus, the optimal clustering of logistics mobility in a metropolitan area was carried out with GIS and a meta-heuristic approach. GIS produced the spatial information needed by p-median model, then the meta-heuristic approach determined the optimal result that considers the logistics costs. BPSO algorithm has employed as the meta-heuristic and it is observed that the algorithm can reach the optimum results within superior times for the problem sizes tested where binary integer programming verified the optimums and the algorithm continued to reach improved solutions where the exact algorithms failed for larger instances. The integrated solution methodology is applied to a large metropolitan region and it is found that it can be used properly by the urban city planners and supply chain managers to analyze critical nodes of transportation networks of megacities.
Recently, CO2 emissions increase apparently in road freight transportation section accompanied with rapidly development of logistics industries in China. However, many published researches used CO2 emission calculation model to plan the optimized road transportation route regardless of local regulation-compliant constraints. This study fills this gap by improving CO2 emission calculation model for road transportation with several regulation-compliant constraints, such as driving-duration limitation constraint. A transportation route planning case of starting from a logistics hub to a logistics demand node in China is employed to get an optimized Road Freight Transportation Route Strategy (RFTRS). We found that: (1) The CO2 emission calculation model in this research gets rid of lack consideration of regulation-compliant constraints in developed CO2 emission reducing models in the literature. The optimized RFTRS with the lowest CO2 emission is not necessarily meeting driving duration limitation within local traffic regulations and also not with the lowest expenditure in transportation process. (2) The optimized RFTRS should not include too many commodity transfers in intermediate nodes or happen with logistics function nodes in reverse-order. In the case, low carbon emission and regulation-compliant requirements for RFTRS are all achieved simultaneously in the shortest expressway routing scenario. (3) The RFTRS optimization process in the case means that high grade roads, such as expressways, and the shorter length of transportation route are the prior selections.
The following research focuses on the externalities generated on the public transport system, due to the disorder and use of the street section from goods and logistics operators, during the peak hours on the city. Through microsimulation of traffic variables, the mobility issues are characterized in zones with mix uses ground taking in to count some variables such, travel times, combustible consume and emissions in one of the most use corridors in the city of Bogotá. The study of open data, complemented with field information, permit the evaluation of the mentioned parameter tested on the actual infrastructure. It is essential to say that the evaluated corridor is classified into secondary roads in the city and operate almost 22 urban routes of the public transit system.
The paper deals with the integration of data provided from traditional transport surveys (small data) with big data, provided from Information and Communication Technology (ICT), in building Transport System Models (TSMs). Big data are used to observe historical mobility patterns and transport facilities and services, but they are not able to assess ex-ante effects of planned interventions and policies. To overcome these limitations, TSMs can be specified, calibrated and validated with small data, but they are expensive to obtain. The paper proposes a procedure to increase the benefits of TSMs’ building in forecasting capabilities, on one side; and limiting the costs connected to traditional surveys thanks to the availability of big data, on the other side. Small data (e.g., census data) are enriched with Floating Car Data (FCD). At the current stage, the procedure focuses on two specific elements of TSMs: zoning and graph building. These processes are both executed considering the estimated values of an intensity function of FCDs, consistently with traditional methods based on small data. The data-fusion of small and big data, operated with a Geographic Information System (GIS) tool, in a real extra-urban context is presented in order to validate the proposed procedure.
Purpose
This paper investigates the diffusion dynamics of electric and hybrid commercial vans and its enabling factors in city logistics (CL) contexts. The case of parcel delivery in Torino, Italy, is considered. Attention is paid to the influence on the choice of low impact vehicles of not only public strategies but also operational aspects characterising urban freight distribution systems.
Design/methodology/approach
A System Dynamics model based on Bass diffusion theory computes the number of adopters of low emission vehicles together with the quantity of vans required and the associated economic savings. The model includes variables about freight demand, delivery frequency, van carrying capacity, routes, stops, distances travelled, and vehicle charging stations. A sensitivity analysis has been completed to identify the main diffusion levers. The focus is on advertising and other drivers such as public contributions, taxes traditional polluting vehicles are subjected to as well as routing optimization strategies.
Findings
Advertising programs, green image, and word of mouth drive market saturation although in a long time period. In fact, low impact vehicles do not offer any economic advantage over traditional ones requiring higher investment and operating costs. Public incentives to purchase both green vehicles and charging stations, together with carbon taxes and a congestion charge affecting polluting vehicles, are able to shorten the adoption time. In particular, public intervention reveals to be effective only when it unfolds through a number of measures that both facilitate the use of environmentally friendly vehicles and discourage the adoption of traditional commercial vans. Route optimization also hastens the complete market saturation.
Research limitations/implications
This work fosters research about the mutual relationships between the diffusion of low emission commercial vehicles and the operational and contextual CL factors. It provides a structured approach for investigating the feasibility of innovative good vehicles that might be part of assessments of CL measures and requirements. Finally, the model supports studies about the cooperation among stakeholders to identify effective commercial vehicle fleets.
Practical implications
This study fosters collaboration among CL players by providing a roadmap to identify the key factors for the diffusion of environmentally friendly freight vehicles. It also enables freight carriers to assess the operational and economic feasibility of adopting low impact vehicles. Finally, it might assist public authorities in capturing the effects of new urban transportation policies prior to their implementation.
Originality/value
Most of the current CL literature defines policies and analyses their effects. Also, there are several contributions on the diffusion of low emission cars. The present study is one of the first works on the diffusion of low impact commercial vehicles in urban areas by considering the associated key operational factors. A further value is that the proposed model combines operational variables with economic and environmental issues.
The Green Transportation issues are gaining interest from theoretical, political and social perspectives. Freight road transport, that is one important aspect of environmentally responsible logistics, is discussed in depth. The activity of transport causes a high rate of negative effects on the environment, as pollutants emission (greenhouse gas).The immediate consequence of this effects is depletion of ozone layer and climate change, that is the reason why we must been reducing the emissions from the sector. Nevertheless, the classical capacitated vehicle routing problem (CVRP) with the objective of minimizing the greenhouse gas especially the carbon dioxide (CO2), states for the problem of finding routes for vehicles to serve a set of customers while minimizing the CO2 emissions. We present in this paper the technique employed to estimate de CO2 emissions, the emissions matrix and their integration into the CVRP model, then we propose a Hybrid Ant Colony System (HACS) to solve the CVRP with the objective of minimizing the CO2. The effectiveness of our approach is tested on a well-known set of benchmarks. Note that our approach is the first adaptation for this problem by the ant colony system.
This paper presents the application of the new DEMATEL-MABAC model in the process of making investment decisions on the acquisition of manipulative transport (Forklifts) in logistics centers. The DEMATEL method was used to obtain the weight coefficients of criteria, on the basis of which the alternatives were evaluated. The selection of criteria for evaluating Forklifts was based on an analysis of available literature. The evaluation and selection of Forklifts was carried out using a new multi-criteria method - the MABAC (Multi-Attributive Border Approximation area Comparison) method. This paper presents a practical application and a sensitivity analysis of the MABAC method. The sensitivity analysis was conducted in three stages. In the first stage, a stability analysis was carried out on the solution reached by the MABAC method, depending on changes made to the weights of the criteria. In the second and third stages, a consistency analysis of the results from the MABAC method was carried out depending on both the changes in the measurement units in which the values of individual criteria are presented and on the formulation of the criteria. The SAW, COPRAS, TOPSIS, MOORA and VIKOR methods were tested under the same conditions. Based on the results obtained, it was shown that the SAW, COPRAS, TOPSIS, MOORA and VIKOR methods do not meet one or more of the conditions set, while the MABAC method showed stability (consistency) in its solutions. Through the research presented in this paper, it is shown that the new MABAC method of multi-criteria decision-making is a useful and reliable tool for rational decision-making.
Logistics, especially the city logistics delivery becomes one of the main contributors of energy consumption and environment pollution in urban transportation system. Reasonable vehicle route planning is viewed as an important solution to lower the energy consumption of delivery vehicle as well as reduce logistics enterprises’ operation costs. However, in most existing vehicle routing problem (VRP) studies, the road networks were simplified and the client points were connected by unidirectional roads, which is obviously inconsistent with the actual conditions of road network. A new VRP solution based on a bi-directional road network, which aims to minimizing fuel consumption for gasoline powered delivery vehicle, is proposed in this paper. First, the mathematic VRP model with the minimal-fuel consumption as optimization objective is established. Then, a bi-directional road network for VRP is constructed, and alternative stop point for each delivery client is formulated according to the weight of package and the walking distance of deliveryman. Finally, the proposed method is evaluated in an actual road network, and the results show that the proposed solution for VRP reduces the distance of roundabout and the fuel consumption of delivery vehicle effectively.
Emergency events, such as earthquakes, hurricanes, fires, chemical accidents, nuclear accidents, terror attacks and other events may led to injured or endanger the life and the health of human beings, and the large scale crowds have to evacuate from a danger area to a safe area by vehicles. In this paper, through observing real-time road network and analyzing three different emergency evacuation cases and the nodes, intersections delay and velocity of vehicles evacuation in the morning peak, common and evening peak. A dynamic road network model is built for vehicles evacuation based on Dijkstra algorithm. The optimal evacuation path is proposed in three different cases. The obtained outcomes provide well predictive method and theoretical basis for optimal emergency evacuation path selection and emergency rescue decision in public places, especially for those with high population density. So it seems very meaningful for us to cope with emergency situation or to prevent and mitigate disasters from the crisis events.
Land use planning in a remote desert zone is usually dependent on an efficient corridor and main road network system. In this paper, Geographic Information System (GIS) tools were used to develop a least-cost path for a corridor to link three cities in Sinai Peninsula desert environment. It is supposed to create a backbone for developing the middle part of peninsula by facilitating the transport of mineral resources and accessibility to such region and encourage populating the remote desert city of Nekhel and the coastal cities of Taba and El Shatt. Therefore, such a route should have the least cost and should be protected from the negative impacts that may be caused by the surrounding environment. Environmental and economical factors were integrated through a spatial multicriteria model using the Analytical Hierarchy Process. Cost factors were identified and a cost surface was created for each factor, standardized, weighed and aggregated. Three visions were modelled: an engineering vision, an environmental vision and a hybrid vision. A multicriteria evaluation was used to compare the three routes. The hybrid route was finally recommended.
This paper considers the development of a new measure for evaluating accessibility to emergency services via a road network called critical closeness accessibility (CCA). CCA quantifies the relative importance of each link in a roadway network with respect to its system-wide contribution to emergency service accessibility and is based on the network science / graph theory concept of closeness. CCA is a link-focused measure that used to evaluate accessibility on a link-by-link basis and can be used for disconnected networks. We introduce a relative importance-based weighting approach for both origins and destinations that can be applied to different types of nodes including generic link endpoints that represent individual intersections and roadway segments in GIS-based roadway maps as well as to physical locations. CAA offers a unique approach for evaluating accessibility that accounts for the spatial distribution of emergency service locations, the topology of the road network, and the engineering characteristics of the road network such as road types, capacities, volumes, and travel speeds.
Infrastructure design is always a very complex task because of the many variables involved. Rail design, in particular, takes on considerable importance (together with the socioeconomic variables) among the environmental variables. The latter is a factor that contributes strongly to the definition of design choices. This paper proposes a method for optimizing the choice of the corridors/line of “high speed rail” (HRS). In particular, the method is based on “multi criteria analysis” with GIS support. The method was applied to a real case in order to evaluate its economic feasibility, social and environmental impact. We considered three possible corridors (conservative, compromise and innovative) for the construction of high-speed rail lines in an area located in the south of Italy The analysis performed gave the following results:.a conservative point of view: the better hypothesis was a corridor near the coast but more tortuous; this solution preserves the environment, but involves higher costs and greater “travel time”;an innovative point of view and a compromised point of view: the better hypothesis was a corridor crossing the territory in the central part (central park zone of great importance for the environment).In this case the corridor gives higher speeds and lower “travel times”; however for this solution the environmental components are jeopardized to a greater degree.
The ASSET project (ASsessing SEnsitiveness to Transport) has developed a GIS–based Web–tool using a map database to depict spatial indicators of transport and related pressures and maps on sensitiveness to transport activities. Among the indicators of sensitiveness used in the project there are Human health indicators: impacts due to noise, air pollution and higher concentration levels in cities and valleys. Ecosystem sensitivity indicators: Analysis of habitat sensitivity, landscape fragmentation and configuration of ecosystems. Indication of sensitive areas indicators in terms of scenic landscapes and impacts from tourism. The mapping of transport sensitive areas in Europe can allow for the identification and prioritization of critical sustainability issues geared to the development of the TEN–T network. Furthermore, volumes generated by transport models like TRANSTOOLS for actual situation and scenarios can be confronted with the sensitivity of the areas they cross.
Environmental, social, and political pressures to limit the effects associated with greenhouse gas emissions are mounting. Little research has been done on reducing emissions as the primary objective of a routing problem despite the growth in use and impact of commercial vehicles. In the capacitated vehicle routing problem (VRP) with time windows, it is traditionally assumed that carriers minimize the number of vehicles as a primary objective and distance traveled as a secondary objective without violating time windows, route durations, or capacity constraints. New research focuses on a different problem: the minimization of emissions and fuel consumption as the primary or secondary objective. This creates the emissions V:RP (EVRP). A formulation and solution approaches for the EVRP are presented. Decision variables and properties are stated and discussed. Results obtained with a proposed EVRP solution approach for different levels of congestion are compared and analyzed.
This paper proposes a new cost function based on distance and load of the vehicle for the Capacitated Vehicle Routing Problem.
The vehicle-routing problem with this new load-based cost objective is called the Energy Minimizing Vehicle Routing Problem
(EMVRP). Integer linear programming formulations with O(n
2) binary variables and O(n
2) constraints are developed for the collection and delivery cases, separately. The proposed models are tested and illustrated
by classical Capacitated Vehicle Routing Problem (CVRP) instances from the literature using CPLEX 8.0.
Abstract The weighted linear combination,(WLC) technique is a decision rule for deriving composite maps,using GIS. It is one of the most often used decision models in GIS. The method, however, is frequently applied without full understanding of the assumptions underling this approach. In many case studies, the WLC model has been,applied incorrectly and,with dubious,results because,analysts (decision makers) have ignored or been unaware,of the assumptions. This paper provides a critical overview of the current practice with respect to GIS/WLC and suggests the best practice approach.
This article considers the continuous version of the refueling station location problem on a tree network, which is a common structure in numerous toll roads worldwide, so as to locate a single alternative-fuel refueling station to maximize the traffic flow covered in round trips/day. Two reduction properties regarding the problem size and some optimality conditions are derived. Based on these conditions, an exact polynomial algorithm is developed to determine the set of optimal locations for the refueling station. A small tree network example is solved to illustrate the algorithm.
To achieve sustainability in the area of transport we need to view the decision-making process as a whole and consider all the most important socio-economic and environmental aspects involved. Improvements in transport infrastructures have a positive impact on regional development and significant repercussions on the economy, as well as affecting a large number of ecological processes. This article presents a DSS to assess the territorial effects of new linear transport infrastructures based on the use of GIS. The TITIM - Transport Infrastructure Territorial Impact Measurement - GIS tool allows these effects to be calculated by evaluating the improvement in accessibility, loss of landscape connectivity, and the impact on other local territorial variables such as landscape quality, biodiversity and land-use quality. The TITIM GIS tool assesses these variables automatically, simply by entering the required inputs, and thus avoiding the manual reiteration and execution of these multiple processes. TITIM allows researchers to use their own GIS databases as inputs, in contrast with other tools that use official or predefined maps. The TITIM GIS-tool is tested by application to six HSR projects in the Spanish Strategic Transport and Infrastructure Plan 2005-2020 (PEIT). The tool creates all 65 possible combinations of these projects, which will be the real test scenarios. For each one, the tool calculates the accessibility improvement, the landscape connectivity loss, and the impact on the landscape, biodiversity and land-use quality. The results reveal which of the HSR projects causes the greatest benefit to the transport system, any potential synergies that exist, and help define a priority for implementing the infrastructures in the plan.
The study investigates a practical freight carrier collaboration problem in a carbon-constrained business context. It examines to see if collaboration between carriers can reduce the environmental issues of freight movement. The introduction of carbon credit systems will stimulate freight carriers to decide whether it should trade carbon credits with its collaborators. This issue is examined by formulating the problem as a two-stage stochastic program to minimize the joint emission of the carriers while meeting their service commitments. The collaborative model developed can reduce emissions across a freight network by 3–20%.
The paper considers heterogeneous fixed fleet vehicle routing with carbon emission to minimizing the sum of variable operation costs. A cost-benefit assessment of the value of purchasing or selling of carbon emission rights, using a mixed integer-programming model to reflect heterogeneous vehicle routing, is incorporated. Essentially, the use of a carbon market as a means of introducing more flexibility into an environmentally constrained network is considered. Tabu search algorithms are used to obtain solutions within a reasonable amount of computation time. In particular, we show the possibility that the amount of carbon emission can be reduced significantly without sacrificing the cost due to the benefit obtained from carbon trading.
We address the problem of determining all extreme supported solutions of the biobjective shortest path problem. A novel Dijkstra-like method generalizing Dijkstra׳s algorithm to this biobjective case is proposed. The algorithm runs in O(N(m+n log n)) time to solve one-to-one and one-to-all biobjective shortest path problems determining all extreme supported non-dominated points in the outcome space and one supported efficient path associated with each one of them. Here n is the number of nodes, m is the number of arcs and N is the number of extreme supported points in outcome space for the one-to-all biobjective shortest path problem. The memory space required by the algorithm is O(n+m) for the one-to-one problem and O(N+m) for the one-to-all problem. A computational experiment comparing the performance of the proposed methods and state-of-the-art methods is included.
Likert scaling is one of the oldest and most widely used methods in behavioral science research, and is one of the key methodologies for attitude measurement. Arguably, there are several reasons for Likert scaling’s appeal: the measures that are analyzed (i.e., multiple item questionnaires) are relatively easy to administer, quantify, and code; and the parametric analysis of mean scores is intuitively meaningful. Here, in order to expand the scope of research that can be addressed through these data, we take a vector-space approach to the ordinal data of Likert scaling: the attitudes of individual subjects are defined as vectors in an abstract attitudinal vector space, and we introduce the density matrix as a means of quantifying the statistics of these vectors. We show that the vector-space approach leads naturally to two different types of attitude state, which we define as a mixed attitude state and a coherence attitude state. As we show, coherence attitude states are intimately linked to subjects “being of two minds” with regard to any particular questionnaire item (i.e., marking two as opposed to one response for a questionnaire item). Additionally, we show that a vector-space approach to Likert-scaling leads quite naturally to order-effects, where (for example) primacy arguments for attitude change may or may not prove more persuasive than recency arguments; and we show that a density matrix description of Likert-scale data can lead to a more nuanced assessment of order-effects.
This paper analyzes an integrated inventory control and transportation problem with environmental considerations. Particularly, explicit transportation modeling is included with inventory control decisions to capture per truck costs and per truck capacities. Furthermore, a carbon cap constraint on the total emissions is formulated by considering emission characteristics of various trucks that can be used for inbound transportation. Due to complexity of the resulting optimization problem, a heuristic search method is proposed based on the properties of the problem. Numerical studies illustrate the efficiency of the proposed method. Furthermore, numerical examples are presented to show that both costs and emissions can be reduced by considering heterogeneous trucks for inbound transportation.
Organizations have recently become interested in applying new approaches to reduce fuel consumptions, aiming at decreasing green house gases emission due to their harmful effects on environment and human health; however, the large difference between practical and theoretical experiments grows the concern about significant changes in the transportation environment, including fuel consumptions, carbon dioxide (CO2) emissions cost and vehicles velocity, that it encourages researchers to design a near-reality and robust pollution routing problem. This paper addresses a new time window pickup-delivery pollution routing problem (TWPDPRP) to deal with uncertain input data for the first time in the literature. For this purpose, a new mixed integer linear programming (MILP) approach is presented under uncertainty by taking green house emissions into consideration. The objective of the model is to minimize not only the travel distance and number of available vehicles along with the capacity and aggregated route duration restrictions but also the amount of fuel consumptions and green house emissions along with their total costs. Moreover, a robust counterpart of the MILP is introduced by applying the recent robust optimization theory. Computational results for several test problems indicate the capability and suitability of the presented MILP model in saving costs and reducing green house gases concurrently for the TWPDPRP problem. Finally, both deterministic and robust mathematical programming are compared and contrasted by a number of nominal and realizations under these test problems to judge the robustness of the solution achieved by the presented robust optimization model.
Today’s growth in the level of traffic in cities is leading to both congestion and environmental pollution (exhaust emissions and noise), as well as increased costs. Traffic congestion makes cities less pleasant places to live in, a particular problem being the negative impact on health as a result of increased exhaust emissions. In addition to these emissions, another major effect of transport which can lead to serious health problems is noise (EEA, 2013a, 2013b). There is a strong tendency in the world towards the development of “clean” motor vehicles that do not pollute the environment, that is, that do not emit harmful substances in their exhaust fumes and which create less noise without causing other types of pollution. The growth in the influence of transport on the environment has resulted in planners formulating procedures which take into account the effect of traffic on the quality of life in urban areas. This paper presents a model for the routing of light delivery vehicles by logistics operators. The model presented takes into account the fact that logistics operators have a limited number of environmentally friendly vehicles (EFV) available to them. When defining a route, EFV vehicles and environmentally unfriendly vehicles (EUV) are considered separately. For solving the problem of routing in the model, an adaptive neural network was used which was trained by a simulated annealing algorithm. An adaptive neural network was used for assessing the performance of the network branches. The input parameters of the neural network were the logistics operating costs and environmental parameters (exhaust emissions and noise) for the given vehicle route. Each of the input parameters of the neural network was thoroughly examined. The input parameters were broken down into elements which further describe the state of the environment, noise and logistics operating costs. After obtaining the performance of the network links for calculating the route for EFV and EUV vehicles a modified Clark–Wright algorithm was used. The proposed model was tested on a network which simulates the conditions in the very centre of Belgrade. All of the input parameters of the model were obtained on the basis of 40 automatic measuring stations for monitoring the air quality (SEA, 2012).
Local city authorities are making a serious effort to expand the number of low-greenhouse gas vehicles (green vehicles) at home. There is no reliable methodology, however, to support the implementation of this passenger transportation concept. In order to optimize the green capacity, a system has been developed to support decision making in urban green vehicle routing. The objective of this paper is to propose a green vehicle distribution model in a public transportation network. The problem has been defined as a problem of non-linear optimization with dispersed input parameters, requiring neuro-fuzzy logic. An adaptive neural network was developed, taking into account the costs to be borne by operators and users, and the environmental parameters along the observed vehicle route. Each input parameter of the neuro-fuzzy model has been placed in a complex context. They were divided into the elements describing in more detail the environmental status, the operator and passenger costs. The advantage of the model is that several factors shaping the input parameters have been taken into consideration. On the other hand, the complexity of urban systems management makes it a considerable challenge, and the surrounding circumstances are difficult to predict accurately. Accordingly, the inputs of the green vehicle model were fuzzified. The Index of Performance (IP) is the output, associated with each branch of the passenger transportation network. The model has been tested on a part of the public transport system in central Belgrade. The results have proven a practical application possible, and a calibration of input parameters allows for full implementation in public transport vehicle routing.
In this paper, the decrease in the emission of greenhouse gases is evaluated using the vehicle routing problem with backhauls and time windows by considering the energy required for each route and estimating the load and distance between customers. Using a scatter search, problems from the literature with up to 100 randomly distributed customers were analyzed. Our results indicate that the distance traveled and the transportation costs increase as the required energy decreases, but the amount of fuel consumed also decreases; therefore, the emission of greenhouse gases also decreases. In some cases, the number of vehicles remains the same or increases because a better solution is achieved with shorter, better distributed routes. In addition, using a cooperative game approach, we found that different transportation companies operating jointly results in decreased emissions as well as operating costs.
In the early stages of development, alternative-fuel vehicles will tend to have shorter driving ranges than conventional vehicles, and the availability of stations will be limited. Given these conditions, it is important to consider the willingness of drivers to deviate to some extent from their shortest paths in order to refuel their vehicles and complete their trips. Previously, we proposed the deviation-flow refueling location model (DFRLM) for locating a given number of refueling facilities to maximize the total alternative-fuel vehicle flows that can be refueled by drivers traveling on or deviating from their shortest paths. On a real-world problem, however, the large number of possible deviations from each path and of combinations of facilities that can cover each path would make it extremely difficult to generate and solve the mixed-integer formulation. This paper develops heuristic algorithms for the DFRLM that overcome this difficulty through network transformation. Specifically, a greedy heuristic constructs and edits an artificial feasible network in which each node represents a station, origin, or destination, and each arc represents a feasible path between two nodes given the assumed driving range of vehicles. At each step of the greedy and greedy-substitution algorithms, the feasible network is edited and a shortest path algorithm is run, which determines whether each origin–destination round trip can be completed. This method allows any possible detour to be taken (up to some user-defined maximum) while also ensuring that drivers take the smallest possible detour. Computational experiments on a simple network and a real-world network for Florida show the heuristics to be efficient in solving the problems. Comparisons between the results of the DFRLM and the FRLM indicate that taking driver deviations into account in the model can have a significant effect on the locations chosen and demand covered.
We consider a generalization of the capacitated vehicle routing problem known as the cumulative vehicle routing problem in the literature. Cumulative VRPs are known to be a simple model for fuel consumption in VRPs. We examine four variants of the problem, and give constant factor approximation algorithms. Our results are based on a well-known heuristic of partitioning the traveling salesman tours and the use of the averaging argument.
The paper develops an approach to the time-constrained, multiple-stop, truck-routing problem that minimizes the fuel consumption and pollutants emission. Features of framework are; it minimizes the distance a delivery vehicle must travel with a heavy payload in a given tour by sequencing the customer visits such that heavier items are unloaded first while lighter items are unloaded later, and it considers the amount of fuel burned during the time a truck is detained at customer sites. Our simulations, based on the routing of an actual motor carrier, suggest the approach may produce up to 6.9% in fuel savings over existing methods.
A collection of data analysis procedures is presented which are derived from estimation of geographic interpolation parameters. Several interpolation models are discussed along with a procedure to obtain the best model. The power parameter, p, and the search radius, c, are the standard parameters in inverse distance weighting interpolation which is appropriate for sampling patterns that are not highly irregular. The power parameter is shown to characterize the regional behavior of geochemical measurements. This characterization process can be used to associate similar types of geochemical measurements, produce optimal contour maps, derive meaningful residual maps, and highlight unusual geochemical areas by a weighted sum variable. The computer program. BESTP, (used to estimate the optimum inverse distance weighting interpolation parameters) is presented, along with an example using reconnaissance groundwater data from the Plainview Quadrangle, Texas.
Most Strategic Environmental Assessment (SEA) research has been concerned with SEA as a procedure, and there have been relatively few developments and tests of analytical methodologies. The first stage of the SEA is the ‘screening’, which is the process whereby a decision is taken on whether or not SEA is required for a particular programme or plan. The effectiveness of screening and SEA procedures will depend on how well the assessment fits into the planning from the early stages of the decision-making process. However, it is difficult to prepare the environmental screening for an infrastructure plan involving a whole country. To be useful, such methodologies must be fast and simple. We have developed two screening tools which would make it possible to estimate promptly the overall impact an infrastructure plan might have on biodiversity and global warming for a whole country, in order to generate planning alternatives, and to determine whether or not SEA is required for a particular infrastructure plan.
The present paper adds to the relatively limited empirical literature involving green logistics by comparing US and non-US firms with respect to select propositions regarding environmental issues, practices, and strategies. For a majority of propositions evaluated, the study results indicate that US and non-US firms tend to share similar perspectives and practices regarding the management of environmental logistics. The study results also tend to confirm literature suggestions that green concerns will broaden the scope of logistics as well as influence the way logistics managers do their jobs.
A heuristic algorithm is described for vehicle routing and scheduling problems to minimise the total travel time, where the time required for a vehicle to travel along any road in the network varies according to the time of travel. The variation is caused by congestion that is typically greatest during morning and evening rush hours. The algorithm is used to schedule a fleet of delivery vehicles operating in the South West of the United Kingdom for a sample of days. The results demonstrate how conventional methods that do not take time-varying speeds into account when planning, except for an overall contingency allowance, may still lead to some routes taking too long. The results are analysed to show that in the case study using the proposed approach can lead to savings in CO2 emissions of about 7%.
The Vehicle Routing Problem (VRP) is one of the most challenging combinatorial optimization task. This problem consists in designing the optimal set of routes for fleet of vehicles in order to serve a given set of customers. Almost all the research papers of VRPs focus on minimizing the sum of travel distance (travel time). However, vehicle managers are also interested in the vehicle routing schedules which minimize fuel consumption caused by two factors. First, reducing fuel consumption means reducing the service cost. Second, reducing fuel consumption means reducing its impact on our environment (green-house effect), our health (air pollutants), and our economy (increased fuel prices). This paper provides a new vehicle routing problem based on reducing fuel consumption. That is, the optimization objective of the vehicle routing problem is to minimize the fuel consumption. The paper also gives the corresponding vehicle routing problem, the optimization objective of which is to minimize the travel distance. Through a numerical example, the two problems are compared. The result shows that a different vehicle routing schedule is probable found if the optimization objective is to minimize fuel consumption other than to minimize travel distance.
The amount of pollution emitted by a vehicle depends on its load and speed, among other factors. This paper presents the Pollution-Routing Problem (PRP), an extension of the classical Vehicle Routing Problem (VRP) with a broader and more comprehensive objective function that accounts not just for the travel distance, but also for the amount of greenhouse emissions, fuel, travel times and their costs. Mathematical models are described for the PRP with or without time windows and computational experiments are performed on realistic instances. The paper sheds light on the tradeoffs between various parameters such as vehicle load, speed and total cost, and offers insight on economies of 'environmental-friendly' vehicle routing. The results suggest that, contrary to the VRP, the PRP is significantly more difficult to solve to optimality but has the potential of yielding savings in total cost.
The forecasting of road freight traffic has relied heavily on the close correlation between GDP and road tonne-kilometers. It has not been rooted in an understanding of the causes of freight traffic growth. The research reported in this paper has investigated this process of traffic growth in two ways: first, by analysing official data on the production, consumption and movement of food and drink products, and second, by conducting a survey of the changing freight transport requirements of 88 large British-based manufacturers.The analysis of secondary data shows how, in the food and drink sector, the relationship between the real value of output and road vehicle-kms hinges on four key parameters: value density, handling factor, average length of haul and consignment size. An attempt is made to explain variations in these parameters.The survey of manufacturers suggests that the growth of lorry traffic is the net result of a complex interaction between factors operating at four levels of logistical management: strategic planning of logistical systems, choice of suppliers and distributors, scheduling of product flow and the management of transport resources. Changes in the frequency and scheduling of freight deliveries in response to tightening customer service requirements and just-in-time management appear to have become a more prevalent cause of freight traffic growth than the physical restructuring of logistical systems. Manufacturers anticipate that their road freight demand will broadly increase in line with sales and be largely unaffected by road transport cost increases at the levels currently proposed. The paper concludes by examining their likely reactions to a much sharper increase in the cost of road freight movement.
We consider a graph with n vertices, all pairs of which are connected by an edge; each edge is of given positive length. The following two basic problems are solved. Problem 1: construct the tree of minimal total length between the n vertices. (A tree is a graph with one and only one path between any two vertices.) Problem 2: find the path of minimal total length between two given vertices.
The vehicle routing problem (VRP) has been addressed in many research papers. Only a few of them take time-dependent travel speeds into consideration. Moreover, most research related to the VRP aims to minimize total travel time or travel distance. In recent years, reducing carbon emissions has become an important issue. Therefore, fuel consumption is also an important index in the VRP. In this research a model is proposed for calculating total fuel consumption for the time-dependent vehicle routing problem (TDVRP) where speed and travel times are assumed to depend on the time of travel when planning vehicle routing. In the model, the fuel consumption not only takes loading weight into consideration but also satisfies the “non-passing” property, which is ignored in most TDVRP-related research papers. Then a simulated annealing (SA) algorithm is proposed for finding the vehicle routing with the lowest total fuel consumption. An experimental evaluation of the proposed method is performed. The results show that the proposed method provides a 24.61% improvement in fuel consumption over the method based on minimizing transportation time and a 22.69% improvement over the method based on minimizing transportation distances.
An important concern for any nation wishing to convert to alternate, environmentally friendly energy sources is the development of appropriate fuel distribution infrastructure. We address the problem of optimally locating gas station facilities for developing nations, like India, which are in the process of converting from leaded to unleaded fuel. Importantly, a similar approach may be used in developed countries, which are in the process of converting to automobiles using hydrogen or electrical energy. An integer-programming model with the objective of balancing the perspectives of coverage and cost is presented for this facility location problem. Given the existing network of roads, the model considers the traveling population, the location of existing facilities and the cost of, either converting these facilities to carry unleaded fuel, or of installing new facilities in an attempt to minimize cost and simultaneously maximize coverage of population. We develop a heuristic solution procedure for this problem. The methodology is applied to data sets obtained from Current et al. [J.R. Current, C.S. ReVelle, J.L. Cohon, Decision Sciences 19 (1988) 490] representing the Ohio state limited access highway network, and to the Indian national highway network. Additionally, extensive simulations are carried out in order to examine where our approach compares with the maximum weighted spanning tree approach. This work extends the Maximum Covering/Shortest Path problem (MCSPP) formulated by Current et al. [J.R. Current, C.S. ReVelle, J.L. Cohon, European Journal of Operational Research 21 (1985) 189] to accommodate multiple sources and destinations.
This paper presents a comprehensive spatial model for exploring the interaction between road transportation and environment. The potential negative impacts of transportation on environment can be listed as degradation of air quality, greenhouse gas emissions, increased threat of global climate change, degradation of water resources, noise and habitat loss and fragmentation. Within this interaction, of particular importance is the relationship between urban structure and transport emissions, since it is the urban structure that fundamentally determines transportation demand. Due to the spatial nature of the interaction, Spatial Information Sciences (SIS) has many advantages compared with other systems. The developed model integrates data and methods on spatial bases, detects changes, encompasses monitoring and analyzes the interaction. In order to verify the developed concepts, a pilot project was conducted at the southeast part of Istanbul Metropolitan Area, where the development of motorway and its effects to land use categories between 1987 and 2001 period was analyzed. Within the study area, the road transportation network had been doubled, whereas the construction sites were tripled within the years of 1987–2001. A significant decrease was observed at barren and agricultural land classes. Using the suggested model an integrated framework for exploring the interaction was constituted and the results were discussed.
Fuel consumption accounts for a large and increasing part of transportation costs. In this paper, the Fuel Consumption Rate (FCR), a factor considered as a load dependant function, is added to the classical capacitated vehicle routing problem (CVRP) to extend traditional studies on CVRP with the objective of minimizing fuel consumption. We present a mathematical optimization model to formally characterize the FCR considered CVRP (FCVRP) as well as a string based version for calculation. A simulated annealing algorithm with a hybrid exchange rule is developed to solve FCVRP and shows good performance on both the traditional CVRP and the FCVRP in substantial computation experiments. The results of the experiments show that the FCVRP model can reduce fuel consumption by 5% on average compared to the CVRP model. Factors causing the variation in fuel consumption are also identified and discussed in this study.
The Impact of International Shipping on European air Quality and Climate Forcing
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The timedependent pollution-routing problem
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His work and research interests are primarily focused on the development of interdisciplinary geospatial technologies that include geospatial analysis, spatial statistics, multicriteria decisions, visualization, modeling, spatial military analysis and remotely sensed technologies
- J Ljubomir
Ljubomir J. Gigović was born in Obrovac, Croatia. He received his BS degree from the
Serbian Military Academy, and his MS, PhD degrees in geography from the Faculty of
Geography at the University of Belgrade, 2004, 2008. His work and research interests
are primarily focused on the development of interdisciplinary geospatial technologies that
include geospatial analysis, spatial statistics, multicriteria decisions, visualization, modeling, spatial military analysis and remotely sensed technologies.