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Comparing transportation systems for inter-terminal transport at the Maasvlakte container terminals
Abstract
In this paper, a comparison between three transportation systems for the overland transport of containers between container terminals is presented. A simulation model has been developed to assist in this respect. Transport in this study can be done by either multi-trailers, automated guided vehicles or automated lifting vehicles. The model is equipped with a rule-based control system as well as an advanced planning algorithm. The model is applied to a realistic scenario for the Maasvlakte situation in the near future. The experiments give insight into the importance of the different characteristics of the transport systems and their interaction with the handling equipment. Finally, a cost analysis has been executed to support management investment decisions.
... An MTT is less flexible than an AGV that can perform different transport operations, as it is considered in the approach proposed in this manuscript. Furthermore, the coupling time of the tractor unit to the trailer can result in a slower turn-around time for the vehicles than AGVs, as it is explained by Duinkerken et al. (2007). Another important distinction is that an MTT requires more space as the trailers are coupled, while AGVs are more flexible and only need a space for platoon formation. ...
... In this manuscript and in previous research (Pourmohammad-Zia, Pourmohammad-Zia, Schulte, Souravlias, & Negenborn, 2020), only an exact approach is considered. As shown in the table, most of the papers have proposed deterministic models, and only five of them deal with uncertainty (Cordeau et al., 2015;Duinkerken et al., 2007;Repoux et al., 2021;Scherr et al., 2022;Xiong et al., 2020), as it is done in our research. In terms of the uncertainty approach, this is the only paper proposing a robust optimization approach. ...
... In terms of the scope, a very confined part of the literature on platooning is related to inter-terminal and hinterland transport operations, which is the focus of this manuscript. Inter-terminal problems have been addressed by Duinkerken et al. (2007), Tierney et al. (2014), Zheng et al. (2020), and hinterland transport by Pourmohammad-Zia, Schulte, and Negenborn (2020), Pourmohammad-Zia, Schulte, Souravlias, and Negenborn (2020), Scholl et al. (2022), Xue et al. (2021), You et al. (2020). Seven out of the thirty contributions are focused on port terminals, considering hence, a closed area to operate the automated vehicles. ...
Modern ports face significant challenges as strategic nodes of global supply chains, being responsible for the coordination of inbound and outbound flows at deep-sea and in hinterland transport corridors. Digitization and the adoption of disruptive technologies can help ports to tide over operational challenges. Automated Ground Vehicles (AGVs) are an integral part of operations at many modern ports, especially inside container terminals. With the shift to automated transport outside of the terminal areas, these AGVs may form platoons to establish an efficient port hinterland transport corridor. In this work, we propose a new robust optimization approach to assess the time and cost-efficiency of applying such AGV platoons in a container pickup and delivery problem. We develop a bi-objective mixed-integer programming model, which simultaneously minimizes time and cost elements, and also considers emissions. Each transportation task can be carried out by AGVs or conventional trucks, while the number of available vehicles for each mode is uncertain (as they are used to connect different modalities of container transport). The robust optimization model is based on an ellipsoidal uncertainty set to handle this uncertainty and an augmented epsilon constraint method to obtain Pareto-optimal solutions for this multi-objective problem. The developed framework is evaluated in two case studies: the Port of Rotterdam in The Netherlands and the Port of Valparaíso in Chile, with different traveling distances in corridors to a dry port (200 km) and a pre-terminal (11 km), respectively. The results indicate that the new direct delivery scheme by AGV platoons is significantly more cost- and time-efficient than the benchmark and provides a low-carbon emission transportation mode. While the benefits of decreased dwell times (56% on average) and carbon emissions (on average by 10%) are similar for short and long traveling distances, the savings in cost increase (from 4.9% to 8%) with the increased distance in the Rotterdam case.
... Existing literature focusses on the performance evaluation of one transport mode and finding the ITT fleet configuration with the best performance: minimal number of vehicles needed, highest delivery punctuality, etc. For example, Duinkerken et al. [18] compare three road-based ITT systems (with AGV, ALV, and MTS, respectively) among the Maasvlakte terminals considering the lateness delivery rate. Future research should investigate the integrated ITT fleet with rail, road, and waterway vehicles. ...
... For example, Hu et al. [27] propose a truckbased ITT system connecting 18 terminals in a port area. Duinkerken et al. [18] compare different types of vehicle used in the shared ITT system in Maasvlakte, Rotterdam. In this case, the ITT provider will dispatch the vehicle considering all terminals' transport demand. ...
... Simulation tools are widely used to evaluate the performance of different terminal layout and fleet configuration. For example, Ottjes et al. [8] simulate a multi-terminal system with different factors such as ITT infrastructure, sea berth length, stacking capacity, etc.; Duinkerken et al. [18] test the performance of ITT systems with MTS, AGV, and ALV, respectively. Mixed integer programming (MIP) is usually used to formulate the ITT operations, such as vehicle routing and crane scheduling, and find the optimal plan. ...
Nowadays, the major ports around the world usually consist of multiple terminals and service centers which are often run by different operators. Meanwhile, inland terminals have been also developed to reduce port congestion and improve transport efficiency. The integrated planning of inter-terminal transport (ITT) between the seaport and inland terminals helps in providing frequent and profitable services, but also could lead to higher overall planning complexity. Moreover, the ITT system usually involves multiple stakeholders with different or even conflicting interests. Although an increasing number of studies have been conducted in recent years, few studies have summarized the research findings and indicated the directions for future research regarding ITT. This paper provides a systemic review of ITT planning: we examine 77 scientific journal papers to identify what kind of objectives should be achieved in ITT system planning, which actors should be involved, and what methodologies can be used to support the decision-making process. Based on the analysis of the existing research, several research gaps can be found. For example, the multi-modality ITT systems are rarely studied; cooperation frameworks are needed in the coordination of different actors and quantitative methodologies should be developed to reflect the different actors’ financial interests.
... If gantry cranes are employed, which we presuppose throughout this paper, they span one or two road lanes, where the containers are delivered or received by some container transport device (CTD). The following CTDs are applied for servicing rail yards in seaports (Duinkerken et al. 2006;Tierney et al. 2013;Heilig and Voß 2017): ...
... This way, waiting time for tractor units during the transshipment process by crane is avoided. Multi-trailer trucks are, for instance, applied at the Maasvlakte terminals of Rotterdam (Duinkerken et al. 2006) and the port of Gioia Tauro in Southern Italy (Cordeau et al. 2015). ...
... When supplying a rail yard, initially, a road train has to be loaded with containers in a container yard. Large ports usually consist of multiple container yards, e.g., the stacking yards of different deep-sea and barge terminals, storage areas of truck service centers, and depots for empty containers (Duinkerken et al. 2006). In those yards, road trains are loaded with containers by either gantry cranes or reach stackers. ...
Multi-trailer trucks (also referred to as road trains) consist of a strong tractor truck pulling about a handful of trailers. They are, for instance, used in large ports to collectively transport a batch of containers between different container yards. We address the decision task where to park successive road trains next to some freight trains, so that a gantry crane can quickly transship the boxes between both means of transport. We formalize the resulting optimization problem and derive suited solution procedures. These algorithms are, then, applied to investigate different managerial aspects such as the relation to preceding decision problems, i.e., the composition of road trains, and the road trains’ efficiency compared to conventional (single-trailer) trucks.
... , t 10 , corresponding to a typical working day. We then set the number of jobs to 250 (Duinkerken et al. 2006), and the number of companies to 50, based on the members of the "VZV" (Verenigde Zeecontainer Vervoerders), the Dutch alliance of sea-container carriers, which represents the different carriers in meetings with the terminals, the port, and other entities. ...
... Jobs are distributed over the 10 time periods but not uniformly. Since there are two peak hours throughout the day (Duinkerken et al. 2006), we configure jobs to have a 25% chance of starting at t 2 and another 25% chance of starting at t 6 . If a job would not specifically start at a peak hour, it has an equal chance to start at any time period from t 1 to t 8 . ...
Task allocation problems have traditionally focused on cost optimization. However, more and more attention is being given to cases in which cost should not always be the sole or major consideration. In this paper we study a fair task allocation problem in transportation where an optimal allocation not only has low cost but more importantly, it distributes tasks as even as possible among heterogeneous participants who have different capacities and costs to execute tasks. To tackle this fair minimum cost allocation problem we analyze and solve it in two parts using two novel polynomial-time algorithms. We show that despite the new fairness criterion, the proposed algorithms can solve the fair minimum cost allocation problem optimally in polynomial time. In addition, we conduct an extensive set of experiments to investigate the trade-off between cost minimization and fairness. Our experimental results demonstrate the benefit of factoring fairness into task allocation. Among the majority of test instances, fairness comes with a very small price in terms of cost.
... Decision Support Systems Fazi et al. (2015), Guo et al. (2020), Douma et al. (2012) and van Riessen et al. (2016) 4 OR Spectrum Lee et al. (2006), Kemme (2012), Lee et al. (2014a, b) and Duinkerken et al. (2006) 4 Clott et al. (2015), Williamsson et al. (2020), de Langen et al. (2017 and Baccelli and Morino (2020) 4 Notteboom et al. (2020), Smid et al. (2016), and Zhang et al. (2020) 4 ...
... and Feillet (2014),Li et al. (2015),Li et al. (2014),Shobayo and van Hassel (2019),Caris et al. (2012),Grobarcikova and Sosedova (2016),Gharehgozli et al. (2017),Duinkerken et al. (2006), Dulebenets et al. (2015), Caris et al. (2011), Meers et al. (2018), Douma et al. (2011), Douma et al. (2009), Yahalom et al. (2020), Gumuskaya et al. (2020a, b), Fu et al. (2010), Bouchery et al. (2020), Gracia et al. (2019), Douma et al. (2012), Larsen et al. (2021), Yu et al. (2018), Park et al. (2009), Kemme (2012), Musso and Sciomachen (2020), Zhang et al. (2014), Roukouni et al. (2020), Maione et al. (2016), Boschian et al. (2011), Pant et al. (2011), Zehendner et al. (2015), and Kumawat et al. analysis Castelein et al. (2019), van der Horst et al. (2019), Clott et al. (2015), Roso et al. (2015), Liu et al. (2017), Braekers et al. (2013), Gumuskaya et al. (2020a, b), Williamsson et al. (2020), Ramaekers et al. (2017), Bojić et al. (2020), Kotowska et al. (2018), Baccelli and Morino (2020), Dotoli et al. (2017), Fanti et al. (2017), Kengpol et al. (2012), van Riessen et al. (2016), Bai et al. (2017), Feng et al. (2015), Dai and Yang (2020), Wadhwa et al. (2019), Zhang et al. (2014), Roukouni et al. (2020), Maione et al. (2016), Boschian et al. (2011), and Pant et al. Liu et al. (2017), Fazi and Roodbergen (2018), Braekers et al. (2013), Rajkovic et al. (2016), Kelleher et al. (2003), Fazi et al. (2015), Corman et al. (2017), Li et al. (2015), Li et al. (2014), Clott et al. (2015), Nur et al. (2020), Dotoli et al. (2017), Feng et al. (2015), Dai and Yang (2020), and Wadhwa et al. ...
Container on Barge (COB) facilitates intermodal transportation by transporting shipping containers on barge tows. COB has seen rapid expansion globally over the past 20 years, providing a cost-efficient, environmentally friendly, and congestion-reducing mode of container transportation. European countries have led COB transportation in both study and application over the past two decades. However, increasing interest is observed in both the USA and Asia. In this literature review and comparative analysis, 135 COB-focused peer-reviewed articles are reviewed and analyzed to systematically describe the development and current status of COB transportation research. The relevant literature is analyzed to reveal publication rates and titles, geographical regions of interest, research questions, applied methodologies, advantages of COB transportation, and key success factors. The aim of our effort is to provide information on various aspects of COB development among different regions in the world and to summarize the existing literature to support and guide future COB development.
... Several authors investigate different system approaches with the help of simulation or stochastic models, while considering manned and automated systems. Duinkerken et al. [14], Schroër et al. [15] and Gharehgozli et al. [16], inter alia, use simulation to compare different container transport systems. Those systems are based on existing handling equipment for horizontal container transport in container terminals. ...
... Those systems are based on existing handling equipment for horizontal container transport in container terminals. Duinkerken et al. [14] focus on an object-oriented simulation of multi-trailer systems (MTS), automated guided vehicles (AGV) and automated lift vehicles (ALV) to move containers between two nodes with a maximum distance of 6,000 meters. Schroër et al. [15] investigate alternatives for container transport between the terminals Maasvlakte 1 and Maasvlakte 2 in the Port of Rotterdam using discrete event simulation. ...
The upward trend in global containerized trade is predicted to continue. In addition, increasing ship sizes, growing demand for port-centered value added services and environmental considerations are creating challenges for handling port internal traffic, also referred to as inter-terminal transportation (ITT). Container transports are often carried out by truck, which may lead to congestion in the port area. Due to increasing demand for greater efficiency and for more sustainable and environmentally friendly approaches, new transport solutions receive more attention. In order to strengthen their competitiveness, seaports consider digitalization-driven innovations and technologies and intelligent new concepts to improve the quality and efficiency of port activities, including ITT. The main purpose of the paper is to highlight different approaches to conventional means of land-based transport and future trends.
... Generally, inter-terminal transport (ITT) refers to the container transport between terminals and service centers (e.g., empty depots) using any type of transport modes Duinkerken et al. [1], Heilig & Voss [2]. Moving containers between terminals inside a port might seem unreasonable as it leads to extra service time and cost. ...
... In Hansen [4], self-driven railcars were used to move containers between different rail yards. Duinkerken et al. [1] compared the performance of ITT systems with multi-trailer system (MTS), automated guided vehicle (AGV), and automated lifting vehicle (ALV). In Heilig et al. [2], a cloudbased information platform was introduced. ...
... Conventionally, these inland vessels pickup only containers to/from hinterland. Besides such containers, here we also explicitly consider containers that need to be transported between terminals inside the port area, referred to as inter-terminal transport (ITT) ( Duinkerken, Dekker, Kurstjens, Ottjes, & Dellaert, 2007;Nieuwkoop et al., 2014;Schroer, Corman, Duinkerken, Negenborn, & Lodewijks, 2014;Tierney, Voß, & Stahlbock, 2014). We therefore make a distinction between so-called ITT containers and hinterland containers. ...
... On the other hand, publications on ITT are relatively scarce. The earliest relevant works on ITT are ( Duinkerken et al., 2007;Ottjes, Veeke, Duinkerken, Rijsenbrij, & Lodewijks, 2007), in which the simulation approaches for inter-terminal transportation in the Port of Rotterdam are proposed with the aim to reduce the number of delayed containers that arrived at their destination terminal after the due time. In Schroer et al. (2014), the authors develop a discrete event simulation model for an ITT system in the Port of Rotterdam to evaluate the different ITT vehicles (AGVs, ALVs, MTVs, trucks and barges) configurations defined by Nieuwkoop et al. (2014). ...
Inland vessels are often used to transport containers between large seaports and the hinterland. Each time a vessel arrives in such a port, it typically visits several terminals to load and unload containers. In the Port of Rotterdam, the largest port in Europe, there are 77,000 inland vessels that have moored in the port in 2014 for transporting cargo. With the significant growth of containerized cargo transportation over the last decade, large seaports are under pressure to ensure high handling efficiency. Due to this development and the limited capacity at terminals, the inland vessels usually spend longer time in the port that originally planned. This leads to low utilization of terminal resources and congestion in the port. This paper proposes a novel two-phase planning approach that could improve this, taking into account several practical constraints. Specifically, we take into account the restricted opening times of terminals, the priority of sea-going vessels, and the different terminal capacities and sizes. In addition, we also consider the option for inland vessels to carry out additional inter-terminal transport tasks. Our approach is based on the integration of mixed-integer programming (MIP) and constraint programming (CP) to generate rotation plans for inland vessels. In the first phase, a single vessel optimization problem is solved using MIP. In the second phase, a multiple vessel coordination problem is formulated using CP; three large neighborhood search (LNS)-based heuristics are proposed to solve the problem. Simulation experiments show that the proposed LNS-based heuristic outperforms the performance obtained with a state-of-the-art commercial CP solvers both regarding the solution quality and the computation time. Moreover, the simulation results indicate significant improvements with shorter departure times, sojourn times and waiting times.
... Recent research activities focus on the evaluation of different types of ITT vehicles and vehicle fleet configurations for minimizing delivery delays proposing integer programming (Tierney et al. 2014;Nieuwkoop et al. 2014) and discrete event simulation (Duinkerken et al. 2006;Schroër et al. 2014) approaches (for an extensive bibliography and research agenda on ITT-related research, the reader is referred to Heilig and Voß 2016). However, approaches to efficiently coordinate ITT movements for reducing empty vehicle trips, generating unproductive vehicle emissions and traffic load, have not been considered in the literature so far. ...
... This way, Table 2 shows reasonable parameter values to be assessed during the parameter setting. Once the performance of the hybrid SA for each combination of parameter values has been obtained, the Friedman nonparametric statistical test (Daniel 1990) is used in order to state an order of performances. In those cases in which the null hypothesis of equality of treatments is rejected, the multiple comparisons test of Friedman is used with the aim of determining the differences among combinations. ...
Besides the transport of containers between transshipment areas, an increasing amount of containers needs to be moved to value-added logistics and auxiliary service areas leading to additional container flows within a seaport. Both real-time information exchange and optimization are necessary to efficiently coordinate actors and container movements being involved in respective inter-terminal transport (ITT). However, there is no decision support system facilitating real-time planning and management of ITT taking advantage of modern information technologies and optimization algorithms. In this paper, we formulate the inter-terminal truck routing problem as a novel optimization problem and propose two greedy heuristics and two hybrid simulated annealing algorithms. The computational experiments, conducted using real locations from the Port of Hamburg (Germany), are evaluated extensively. They indicate that the proposed hybrid simulated annealing algorithms are able to report feasible and improved routes within seconds. The optimization component is embedded into a scalable cloud platform that integrates both real-time data from truck drivers using a mobile app and current traffic data. As such, the proposed mobile cloud platform realizes the vision of a decision support system facilitating real-time communication and context-aware ITT planning for reducing costs and the carbon footprint.
... Due to their large capacity road trains can be an efficient means of transport for executing these inter-terminal container exchanges. The Maasvlakte terminals of Rotterdam (Duinkerken et al. 2006) and the port of Gioia Tauro in Southern Italy (Cordeau et al. 2015) are examples for the application of multi-trailer trucks for inter-terminal transports. ...
... The fleet sizes determined for road trains are compared to those required for conventional trucks. Duinkerken et al. (2006) treat the same planning task for Rotterdam's Maasvlakte terminals by means of simulation. They integrate all alternative transport vehicles and their conclusion is that road trains are efficient for processing the basic load of container moves, but not flexible enough during peak hours. ...
An efficient integration of rail transport into the hinterland traffic is an important topic for ports all around the world. In this context, we treat a scheduling problem where multi-trailer trucks (denoted as road trains) deliver containers to some gantry crane, which successively loads the boxes onto freight trains. A road train carries up to a dozen containers, so that a lot of energy is consumed especially when setting a road train in motion. Thus, there is a basic trade-off between the effort of road train and gantry crane. The more often a road train is relocated, the higher its own demand for energy, but the lower that for moving the crane when processing containers rather from nearby holding positions and vice versa. This paper formalizes the novel problem setting and suggests a heuristic decomposition approach, which determines the stop locations of the road train and schedules the gantry crane during the loading process.
... To the best of our knowledge, the paper presents the first approach of utilizing the scalable nature of cloud environments for implementing high performance data-driven ITS. We see a lot of application potential for data-driven ITS in the domain of maritime shipping and especially in port areas such as with respect to inter-terminal transport (ITT) operations (see, e.g., [12,32,33]), which are highly affected by massive traffic volumes, traffic congestions, and pollution. Therefore, we discuss the contribution of cloud-based data-driven ITS to establish intelligent transport infrastructures and to enable smart traffic management and control. ...
... Consequently, an ITS could not only be used to support operational decisions, but also tactical and strategic decisions such as related to investments in port equipment and infrastructure. In the port area, this is especially important for ITT operations (see, e.g., [12,32,33]), where intermodal freight transport activities carried out by multiple actors have to be coordinated between port facilities given internal data sources (e.g., position of trucks, container arrival) and external data sources (e.g., traffic situation, weather). ...
Recent and future technology development make intelligent transport systems a reality in contemporary societies leading to a higher quality, performance, and safety in transportation systems. In a big data era, however, efficient information technology infrastructures are necessary to support real-time applications efficiently. In this paper, we review different control structures based on model predictive control and embed them in cloud infrastructures. We especially focus on conceptual ideas for intelligent road transportation and explain how the proposed cloud-based system can be used for parallel and scalable computing supporting real-time decision making based on large volumes and a variety of data from different sources. As such, the paper provides a novel approach for applying data-driven intelligent transport systems that utilize scalable and cost-efficient cloud infrastructures based on model predictive control structures.
... Since ITT forms a complex network, it needs to be handled efficiently; otherwise, it can be a significant source of transport-related costs. According to Duinkerken et al. [6] and Tierney et al. [7], an efficient ITT system's main objective is to reduce, minimize, or eliminate transport delay. Another objective of an efficient ITT system is to minimize both transport costs and empty-truck trips [2]. ...
Many ports worldwide continue to expand their capacity by developing a multiterminal system to catch up with the global containerized trade demand. However, this expansion strategy increases the demand for container exchange between terminals and their logistics facilities within a port, known as interterminal transport (ITT). ITT forms a complex transportation network in a large port, which must be managed efficiently given the economic and environmental implications. The use of trucks in ITT operations leads to the interterminal truck routing problem (ITTRP), which has been attracting increasing attention from researchers. One of the objectives of truck routing optimization in ITT is the minimization of empty-truck trips. Selection of the transport order (TO) based on the current truck location is critical in minimizing empty-truck trips. However, ITT entails not only transporting containers between terminals operated 24 h: in cases where containers need to be transported to a logistics facility within operating hours, empty-truck trip cost (ETTC) minimization must also consider the operational times of the transport origin and destination. Otherwise, truck waiting time might be incurred because the truck may arrive before the opening time of the facility. Truck waiting time seems trivial, but it is not, since thousands of containers move between locations within a port every day. So, truck waiting time can be a source of ITT-related costs if it is not managed wisely. Minimization of empty-truck trips and truck waiting time is considered a multiobjective optimization problem. This paper proposes a method of cooperative multiagent deep reinforcement learning (RL) to produce TO truck routes that minimize ETTC and truck waiting time. Two standard algorithms, simulated annealing (SA) and tabu search (TS) were chosen to assess the performance of the proposed method. The experimental results show that the proposed method represents a considerable improvement over the other algorithms.
... The monorail system project at Busan Port is a kind of Inter Terminal Transport (ITT) system motivated by similar transport systems in the world [1][2][3][4] . As described in Figure 1 5 , an ITT system is an integrated transport system that would exploit usage of facilities in container port (container terminals, shipping stations, service stations, transport terminals, valueadded facilities, warehouses and depots …) in order to maximize port's throughput 6,7 , which might be up to millions of TEUs (Twenty-feet Equivalent Units) each year at major container ports in the world 8 . About simulation and optimization approaches for ITT system, many studies have been made based on the model of Port of Rotterdam (Maasvlakte I & II Project 9,10 ), since it is the largest container port in Europe with many transport modes (railway, roadway, seaway) and vehicle types (MTS, AGV, ALV, barge, vessel, train…) 10 . ...
This paper presents an optimal solution for handling tasks at Busan Container Port in South Korea. Currently, there is a monorail transportation system being constructed and supposed to be ready in use in 2045. It is a project in association with Korean Government that aims to increase the utility rate at Busan Port – one of the biggest container port in the world. At the moment, the main transport mean at Busan Port is truck – whose speed is about 40-50 km/h, however this traditional method leads to a low productivity and traffic congestions on the road. An innovation is to build a monorail system that could operates at high speed (about 80-90 km/h) along the entire port to transfer standardized containers. This new transportation system is expected to strongly reduce the delay in transporting as well as increase the overall efficiency for the system. In new system, there are transport vehicles called shuttles that would move on the rail in only one direction, and to turn back in the opposite way, there are some special stations called change stations that would direct the shuttles into the other lanes – which is similar to the lane driver systems on the railway. Containers at each inner terminal in Busan Port will be grabbed onto the shuttles by special equipments called loaders – a kind of giant automated manipulator that would load or unload whenever a shuttle requires. To optimize the operation, we introduce a heuristic algorithm called Greedy Algorithm for scheduling tasks and assigning tasks – two major actions in a cycle work that significantly affects to the system’s performance. First, the containers at each loader position will be sorted in a proper sequence, and then the sorted schedule will be assigned to proper shuttles in order to lower the total working time and delay time as much as possible. The overall performance is simulated by MATLAB software, including the result charts showing the main criteria points, in order to highlight the advantage of new transportation system.
... More specific reviews include topics like smart technologies (Cimino et al. 2017) and future challenges (Kim and Lee 2015). Typically, research areas at container terminals include scheduling and routing (Stahlbock and Voβ 2008;Fazlollahtabar and Saidi-Mehrabad 2015), dispatching (Grunow et al. 2004;Garro et al. 2015), port management (Wibowo et al. 2015), terminal configuration and planning (Sun et al. 2013;Mes and Douma 2016), container stacking policies (Dekker et al. 2007;Park et al. 2011), inter-terminal cooperation (Nabais et al. 2013), yard crane scheduling (Fotuhi et al. 2013;Gharehgozli et al. 2015), transportation systems (Duinkerken et al. 2006), collision avoidance (Marinica et al. 2012), deadlocks (Lehmann et al. 2006), control hierarchies (Zheng and Negenborn 2014) and bay planning (Parthibaraj et al. 2017). Moreover, the impact of AGVs or ASCs has been extensively researched. ...
... He et al., 2015;Guo and Huang, 2012;Dai et al., 2004;Liu et al., 2002) or horizontal transport (i.a. Garro et al. 2015;Tao and Qiu, 2015;Duinkerken et al., 2007). Other simulation models consider container terminals as a whole, but focus on medium to large seaport container terminals and do not offer the flexibility required for inland terminals or intermodal terminals. ...
When a new logistic node (e.g. a terminal) is planned or needs to be optimized, layout planning and simulation analysis are typically two separate tasks. While layout planning is an intuitive and visual but static approach, simulation is dynamic but more complex. Integrating both approaches would be highly beneficial. The idea of the integrated tool is to create first a static layout on a touchscreen planning table. After inserting relevant parameters and selecting preferred logistic
strategies, the layout is converted directly into an executable simulation
model. Based on the simulation, e.g. different layout or equipment variations can be tested.
Main challenges for a successful integration are the logistic processes and strategies on the terminal. Both are not included in the layout planning, but are essential for a valid and realistic simulation model. Therefore, relevant process and strategy variations as well as typical research questions are defined. The integrated approach is an innovative solution to optimize planned as well as existing terminals.
Typically, conducting layout planning and simulation studies separately is a very time consuming task. Integrating both is more efficient, closer to reality and more cooperative by allowing to involve more stakeholders at an earlier stage.
... Duinkerken et al. [19] proposed a rule-based simulation model to evaluate three different transportation systems: multi trailer systems (MTSs), automated guided vehicles (AGVs), and automated lift vehicles (ALVs) in Rotterdam's Maasvlakte port area. The simulation experiments provide essential insights into three different characteristics of these transportation systems, including an evaluation of the performance and nonperformance of ITT, utilization of transport vehicles with and without advanced planning, and cost analysis to support investment decisions. ...
The continued growth of the volume of global containerized transport necessitates that most of the major ports in the world improve port productivity by investing in more interconnected terminals. The development of the multiterminal system escalates the complexity of the container transport process and increases the demand for container exchange between different terminals within a port, known as interterminal transport (ITT). Trucks are still the primary modes of freight transportation to transport containers among most terminals. A trucking company needs to consider proper truck routing planning because, based on several studies, it played an essential role in coordinating ITT flows. Furthermore, optimal truck routing in the context of ITT significantly affects port productivity and efficiency. The study of deep reinforcement learning in truck routing optimization is still limited. In this study, we propose deep reinforcement learning to provide truck routes of a given container transport order by considering several significant factors such as order origin, destination, time window, and due date. To assess its performance, we compared between the proposed method and two approaches that are used to solve truck routing problems. The experiment results showed that the proposed method obtains considerably better results compared to the other algorithms.
... ITT system is a system that links the components of a container port (depots, container yards, terminals, etc.) with corresponding transport modes (Duinkerken et al., 2006;Rodrigue at al., 2017;Lee et al., 2012;Zhen et al., 2016) so that it can exploit the capability as much as possible. Major ports usually have many different types of terminal (sea terminal, barge terminal, railway terminal, etc.) with many different transport modalities (road, rail, sea, etc.) (Heilig & Voß, 2017). ...
This paper proposes a heuristic approach named A* algorithm to find shortest route for Inter-Terminal Transport Monorail System (ITT system) that are being applied in Busan Port (Korea). In every transport system, vehicle routing and task assignment are significant problems that affects strongly the overall system’s efficiency, especially the travel cost and the time taking. The proposed ITT system will use shuttles to carry containers along a monorail that links the internal terminals. A* algorithm is used to guide the shuttles in a shortest way automatically from a known loading position to a designated unloading one. In the first part of the paper, we will describe briefly about the ITT system that being considered in Korea. Next, we will explain why and how we implement A* algorithm in dispatching. Finally, we will give some comparisons between performances of new ITT system and traditional transport system through simulation in MATLAB.
... Another stream of research focuses on evaluating design decisions of isolated systems. Using detailed simulation models, researchers have studied the performance and cost trade-offs using different types of vehicles for interterminal container transport: multitrailers, automated guided vehicles, or automated lift vehicles (see Harika 2004 andDuinkerken et al. 2007). Stochastic models have also been used to carry out performance analysis of specific container terminal design aspects. ...
The design of container terminal operations is complex because multiple factors affect operational performance. These factors include numerous choices for handling technology, terminal topology, and design parameters and stochastic interactions between the quayside, stackside, and vehicle transport processes. In this research, we propose new integrated queuing network models for rapid design evaluation of container terminals with automated lift vehicles and automated guided vehicles. These models offer the flexibility to analyze alternate design variations and develop insights. For instance, the effect of different vehicle dwell point policies and efficient terminal layouts are analyzed. We show the relation among the dwell point–dependent waiting times and also show their asymptotic equivalence at heavy traffic conditions. These models form the building blocks for design and analysis of large-scale terminal operations. We test the model efficacy using detailed simulation experiments and real-terminal validation.
... Literature on ACTs is abundant and focuses on topics like routing [1][2][3][4], dispatching [5][6], deadlocks [7][8], container stacking [9][10], yard cranes [11][12] and transportation systems [13][14]. Moreover, the impact of autonomous solutions for horizontal transport (e.g., AGVs or automated straddle carriers) has been explored by many researchers. ...
... He et al., 2015;Guo and Huang, 2012;Dai et al., 2004;Liu et al., 2002) or horizontal transport (i.a. Garro et al. 2015;Tao and Qiu, 2015;Duinkerken et al., 2007). Other simulation models consider container terminals as a whole, but focus on medium to large seaport container terminals and do not offer the flexibility required for inland terminals or intermodal terminals. ...
... The implementation of a multi-modal ITT system among several terminals usually requires coordination between terminal operators and the port authority. Duinkerken et al. (2006), proposed an ITT system which is shared among the terminals at the Maasvlakte, Rotterdam. investigated the truck-based ITT system provided by a third party ITT provider. ...
This paper investigates the problem of inter-terminal movements of containers and vehicles within a port area in order to achieve an integrated and effective transport within the port and towards the hinterland. Containers from different port terminals are first moved to a rail yard and then delivered to the hinterland by rail. To provide insights for stakeholders such as port authority and terminal operators into tactical planning problems, e.g., the coordination between terminals, railway timetable and train sizes, this paper proposes an optimization model describing the movement of containers and various vehicles between and inside terminals. The model aims at improving the container delivery from container terminals to the hinterland considering both railway hinterland transport and terminal handling operations. A network inspired by a real-life port area and its hinterland is used as a test case to test different components, i.e., inter-terminal transport connections, train formation, railway timetable. A rolling horizon framework is used to improve the computation efficiency in large transport demand cases. The result of the optimization helps in identifying the most promising features, namely, that more connections between terminals and a flexible outbound railway timetable could contribute to improving the integrated container transport performance.
... Other than the above-mentioned simulation models, many other CT simulation models have been developed for various decision-making purposes. 25 Among these models, some were dedicated to simulating certain subsystems for particular purposes, such as evaluating the effectiveness of proposed strategies, [26][27][28][29] improving terminal capacity 30 and predicting ship traffic 31 or container flows. 32 To realistically depict the whole terminal operations in real life, several articles developed comprehensive simulation models for a one-berth terminal 2,18,33,34 and multi-berth terminals. ...
The ever-increasing worldwide container throughput and the intensified port competition have demanded better terminal operational performance, which is usually measured by the gross crane rate (GCR). In this paper, a multiagent-based simulation model is proposed to investigate how the block length of the storage yard and the tactical-level stacking policy affect the operational performance of non-transshipment container terminals over the long term. Experiments consider seven block lengths, two yard truck fleet sizes and two stacking policies. The results demonstrate that the best block length yielding the highest GCR is dependent on the stacking policy and the yard truck fleet size, and the separate stacking policy is essentially superior to the scattered stacking policy. Specifically, only when 9-yard trucks are deployed per quay crane under the separate stacking policy, can the typical 42-slot block length achieve the highest GCR. Although the experiments are not exhaustive, they do provide the first fundamental insights, with respect to the effects of block lengths and stacking policies, on the long-term performance at a manually controlled non-transshipment container terminal.
... The second stream of research focuses on evaluating design decisions of systems in interaction. Using detailed simulation models, researchers have studied the performance and cost trade-offs using different type of vehicles for intra-terminal container transport: multi-trailers, automated guided vehicles (AGVs) or ALVs (see Duinkerken et al. [2007], Vis and Harika [2004]). Simulation models developed to analyze operational rules such as the effect of vehicle dispatching policies, e.g., by De Koster et al. [2004]. ...
With the growing worldwide trade, container terminals have grown in number and size. To increase operational efficiency, many new terminals are now automated. The key focus is on improving seaside processes, where a distinction can be made between single quay crane operations (all quay cranes are either loading or unloading containers) and overlapping quay crane operations (some quay cranes are loading while others are unloading containers). Using a network of open and semi-open queues, we develop a new integrated stochastic model for analyzing the performance of overlapping loading and unloading operations that capture the complex stochastic interactions among quayside, vehicle, and stackside processes. The analytical model is solved using an iterative algorithm based on the parametric decomposition approximation approach. The system performance is tested at varying container traffic levels. We find that the percent absolute errors in throughput times compared to simulation are less than 10% for all cases. Using these integrated models, we are able to generate design insights and also rapidly analyze what-if scenarios. For example, we show that the best yard layout configurations for single (either loading or unloading) operations and the best for overlapping (both loading and unloading) operations largely overlap. The best configurations have relatively few stack blocks and many rows per block. The model is generic and amenable to obtain other design and operational performance insights.
... However, sources do not provide consumption values for every single functional unit and existing information exclude terrain conditions or terminal layout within consumption data. This contribution points out in which way energy consumption values are allocated on loading unit level by using energetic simulation based on selective measurements energetic simulation in combined transport simulation is a preferred instrument for examination and evaluation of operations in course of time within multimodal handling terminals [8,14,15]. ...
... The overview indicates that the environmental perspective on ITT operations is currently not considered in the proposed optimization and simulation models. The optimization models for ITT planning predominantly aim to provide decision support to select transport options that minimize the costs and late arrival penalties based on different transport demands (see, e.g., Duinkerken et al., 2006;Tierney et al., 2014). Recently, collaborative planning (Kopfer et al., 2016) and vehicle sharing (He et al., 2013) have been considered as a means for ITT optimization. ...
A tremendous growth in containerized trade has led to severe traffic problems in urban port areas associated with negative effects on both efficiency and pollution. In this paper, we address the multi-objective inter-terminal truck routing problem by specifically considering truck emissions. We present an efficient multi-objective archived simulated annealing approach and a visualization technique. Managerial insights are discussed based on an analysis of trade-offs. The algorithm is embedded in a cloud-based decision support system to consider contextual data, including traffic data and the current positions of trucks. This allows ports to utilize potentials of digitalization and optimization while addressing environmental issues.
... An example of this is interterminal transport (ITT) (Duinkerken et al., 2007;Nieuwkoop et al., 2014;Schroer et al., 2014;Steenken, Voß, and Stahlbock, 2004). The goal of ITT is bundling of the transport movements within a port. ...
The economic relevance of ports is related to the flows of goods they can handle and move, and it is strongly related to economic development. Due to trends in increasing port size, the effect of port size on economies of scale, and the tendency to bundle demand and operations into very large ports, port equipment and its management is becoming crucial for a port's efficiency.
This article reviews the equipment and technology used at ports, with a major focus on containerized and dry bulk transport. An outlook over the future of port equipment points out their efficient management, with a clear trend for increasing support from information–communication technology and automation. This happens at the level of individual machines, as well as at the level of stakeholders (community systems). Via the intelligent interaction of technology and equipment in a coherent integrated system, efficient inter‐ and intraterminal operations can be achieved.
... The second stream of research focuses on evaluating design decisions of systems in interaction. Using detailed simulation models, researchers have studied the performance and cost trade-offs using different type of vehicles for intra-terminal container transport: multi-trailers, automated guided vehicles (AGVs) or ALVs (see Duinkerken et al. [2007], Vis and Harika [2004]). Simulation models developed to analyze operational rules such as the effect of vehicle dispatching policies, e.g., by De Koster et al. [2004]. ...
With growing worldwide trade, container terminals have grown in number and size. Many new terminals are now automated to increase operational efficiency. The key focus is on improving seaside processes, where a distinction can be made between single quay crane operations (all quay cranes are either loading or unloading containers) and overlapping quay crane operations (some quay cranes are loading while others are unloading containers). From existing studies, it is not clear if the design insights obtained from analyzing single operations, such as optimal stack layout, are consistent with the insights obtained from analyzing overlapping operations. In this paper, we develop new integrated stochastic models for analyzing the performance of overlapping loading and unloading operations that capture the complex stochastic interactions among quayside, vehicle, and stackside processes. Using these integrated models, we are able to show that that there are stack layout configurations that are robust for both single (either loading or unloading) and for overlapping (both loading and unloading) operations.
... The proposed integer program can be used either at a strategic level or at an operational level, to minimize delays. Other studies, such as the ones by Duinkerken et al. (2007), Ottjes et al. (2007), provide simulation models of multi-terminal systems and ITT, to support investment decisions. ...
This paper introduces an optimization model of a multi-terminal, multi-modal maritime container port, such as the ones in the European northern range. The decisions concern the scheduling of ships, trains and trucks on terminals, while limiting inter-terminal transport of containers and minimizing weighted turnaround time. Heuristics based on the decomposition of the resulting mixed-integer program are proposed and tested on realistic generated instances with up to four terminals. The efficiency of the restrict-and-fix heuristic
allows to investigate the impact of a global management on port’s performance: an average improvement of 5% was observed.
... Duinkerken et al. [17] used simulation to analyze three ITV types: YTs, AGVs, and ALVs. The objective minimized the overall idle time of QCs. ...
Taking into account increasing volumes of the international seaborne trade and increasing port congestion, marine container terminal operators have to improve efficiency of their operations in order to provide timely service of vessels and avoid product delivery delays to customers. This paper focuses on improvement of container transfer operations between the seaside and the marshaling yard and proposes five yard truck deployment strategies. Performance of the considered marine container terminal is evaluated under each one of the yard truck deployment strategies via simulation. Different performance indicators are estimated to determine how the suggested yard truck deployment strategies will affect all equipment types, involved in container handling and transfer. Results from the extensive simulation experiments showcase that all five yard truck deployment strategies provide similar values of vessel service and quay crane performance indicators, while the shortest distance based yard truck deployment strategy yields superior gantry crane and yard truck performance indicators. The worst values of performance indicators are recorded for the random yard truck deployment strategy. Furthermore, the developed simulation model can serve as an efficient planning tool for marine container terminal operators and enhance productivity of the available equipment.
... For example, many simulation studies focus on the number of containers arriving late at their destination terminal (e.g. Duinkerken et al. 2006;Ottjes et al. 2006). Simulation models can capture many details of the ITT operations but, in order to decide feasibility of an ITT concept, we have to validate it from the perspective of stakeholders, usually monetarized in terms of cost and profit. ...
Major ports contain multiple container terminals, sea terminals, train, truck and barge terminal, and empty container depots, operated by different companies. Port authorities try to streamline inter terminal container transport (ITT) within congested port areas by offering expensive common road and rail infrastructure. Alternatively, individual stakeholders can set up private or collaborative container transport systems. This paper develops a framework to analyse and determine feasibility conditions of a common ITT system in a port area, depending on total transport volumes. First, we develop a simulation model to evaluate the costs of transporting containers using different modes of transport including trucks, automated guided vehicles, and multi trailer systems. Next, the required number of vehicles per mode is determined for a given throughput and waiting time. The results of the simulation are used in a game-theoretic setting to determine the cost savings per stakeholder operating in a coalition. By comparing cost savings for all possible coalitions, it is possible to determine, for each stakeholder, the attractiveness of using a common system. We find the coalitions that result in the highest savings and compare them with the infrastructure cost required to realise them. We apply the method to determine the feasibility of a common ITT system for terminals in the Port of Rotterdam and show that it only pays off in case of high demand for container transports.
... Containers are often transferred between terminals when they are transshipped between different modes of transportation. This type of movement is called inter-terminal transportation (ITT) [5,10,13,14]. There is a range of types of vehicles for ITT, including railway, truck, and container ships, each coming with its advantages and disadvantages. ...
Large seaports usually contain multiple terminals serving container vessels, railways, trucks and other modes of hinterland transportation. Every time an inland vessel enters a seaport, it visits several terminals for loading and unloading containers. A vessel rotation is the sequence in which a vessel visits the different terminals in a large seaport. Currently, in a seaport like the port of Rotterdam, around 40 % of the inland vessels have to spend a longer time in the port area than originally planned, due to the low utilization of terminal quay resources and uncertainty of waiting times at different terminals. To better utilize the terminal resources in the ports, as well as to reduce the amount of time inland vessels spend in the port area, this paper first proposes a new model in which inland vessels coordinate with each other with respect to the arrival, departure time and the number of inter-terminal containers carried, besides their conventional hinterland containers, with the aim to prevent possible conflicts of their rotations. Then, a logic-based Benders’ decomposition approach is proposed to minimize the total time the inland vessels spent in the port. We compare the performance of the proposed approach with the performance of a centralized approach on the aspects of the runtime, solution quality, and three logistical performance indicators. Simulation results show that the proposed approach generates both faster optimal and faster high-quality solutions than the centralized approach in both small and large problem instance.
... No trabalho de [12] e [13], se apresentam estudos sobre contêineres e sistemas de transporte interterminal. Nestes dois estudos, os experimentos realizados mostram as diferentes características dos sistemas de transporte e sua interação com os equipamentos de manuseio. ...
... Simulation is a preferred instrument for examination and evaluation of operations in course of time within multimodal handling terminals (e.g. Lampe 2006; Lee et al. 2006;Duinkerken et al. 2006). Simulation solutions for holistic mapping of multimodal terminals have been developed by the authors in previous research. ...
The assessment of emissions caused by logistics operations in general and their allocation to individual customers is a major challenge for logistics service providers. Presently, numerous standards and guidelines exist (e.g. ISO 14064-1, ISO 14065, DIN EN 14040) for the calculation of GHG-emissions caused by logistics processes. Due to missing or incomplete approaches, the assessments as well as regular updates are quite expensive and time-consuming. This endangers in particular the competitiveness of sme logistics service providers who need to gather and provide the relevant information for their clients.
... Constraints (9) ensure that a ship v ∈Ṽ is handled in only one quay segment. Constraints (10) enforce that moving between two quay segments requires a number of periods. Technical constraints (11)-(13) together with constraints (10) link values of variables h t vz , p t vz and h t vz (the proof is provided in appendix B). ...
... Whereas the main goal of efficient ITT systems is a punctual delivery of containers, for example, to minimize the outgoing vessels' time in port, it becomes increasingly important to consider the economic and environmental impact of ITT. Recent research activities focus on the evaluation of different types of ITT vehicles and vehicle fleet configurations for minimizing delivery delays proposing integer programming (Tierney et al., 2014;Nieuwkoop et al., 2014) and simulation (Duinkerken et al., 2006;Schroer et al., 2014) approaches (for an extensive overview, the reader is referred to Heilig and Voß, 2016). However, empty vehicle trips, generating unproductive vehicle emissions and traffic load, are not considered by these studies. ...
The role of ports goes far beyond the traditional function of a pure transport node linking sea and landside transportation. Rather, many ports offer value-added logistics and auxiliary services leading to a network of container flows. Moreover, containers may need to be transferred between different areas within the port. Information exchange and optimization is necessary to efficiently coordinate actors and container movements involved in respective inter-terminal transports in order to avoid empty trips and thus high costs, emissions, and additional traffic volume. In this paper, we describe a novel optimization problem for addressing inter-terminal truck routing in ports and propose two greedy heuristics and a hybrid simulated annealing algorithm. The computational results are evaluated in terms of costs, empty trips, and utilized number of trucks and they indicate that the proposed hybrid simulated annealing algorithm is able to report feasible and improved routes within seconds. The optimization component is embedded into a cloud platform integrating truck drivers based on a mobile application. Beyond common functionalities, the proposed platform enables a flexible real-time assignment of truck drivers to container movements by considering the current position of trucks with the objective to better manage and coordinate inter-terminal transports. As such, our approach contributes not only with a valuable approach for vehicle planning in ports, but also presents an accessible, scalable, and multi-tenant system prototype of a mobile cloud platform for handling the interactions with truck drivers in practice, demonstrated with an example for the Port of Hamburg, Germany.
... Traditionally, the ship-berth link is one of most critical aspects to be managed at port operations. Until now, simulation models for SBL planning have considered assigning inbound ships to berthing positions and scheduling quay-cranes (Meisel and Bierwirth, 2009), the yard operations (Chang, 2005; Tu and Chang, 2006), railway lines and congestion level of truck gates (Parola and Sciomachen, 2005), transport systems and their interaction with handling equipment (Duinkerken et al., 2006; Ottjes et al., 2006) and etc. To improve the competitiveness of a port, the major task of SBL operation is to allocate a limited number of berths among inbound ships (Wanke, 2011) to reduce the waiting time of ships. ...
This paper explores the effect of entrance channel dimensions on berth occupancy of a container terminal when making master planning for a new container terminal, to avoid possible bottlenecks for port's future performance. Therefore, a process-interaction-based simulation model is first developed to simulate container terminal operation, especially ship operation in entrance channel. Then a series of simulation experiments are conducted, in which dozens of container terminals with different numbers of berths and channel dimensions are considered to reproduce the microscopic, stochastic, real-time environment. Finally, simulation results show that the berth occupancy depends on entrance channel dimensions, and more berths, two-way traffic channel and less travel time in channel have higher berth occupancy given the same port service level. So that the effect of entrance channel dimensions, especially very long one-way traffic channels, on berth occupancy should be quantified when determining berth capacities at the master planning stage. Moreover, the analysis and simulation model presented in this paper may help port authorities and the planners to achieve a harmonized overall design in practice.
The demand for transport between terminals within port areas, known as inter terminal transportation (ITT), is increasing. This paper proposes a dynamic rolling horizon scheduling strategy for ITT using a fleet of waterborne Autonomous Guided Vessels (waterborne AGVs). The strategy is dynamic in that it can handle dynamically arriving ITT requests. Every certain period of time, transport schedules are updated according to the current vessel states, dynamic waterway transport network, and ITT requests over a future time horizon. Specifically, the dynamic scheduling problem is mathematically modeled in a rolling horizon fashion considering time windows of ITT requests, capacity limits of waterborne AGVs and load/unload service times at terminals. Considering the computational complexity for possible large scale ITT scenarios, we further propose an efficient solution approach based on improved insertion, tabu search and restart heuristics. Initial routes are first constructed by inserting new ITT requests into the previously computed routes in the rolling horizon framework. Tabu search with two types of neighborhoods are then designed to improve the initial routes. Moreover, a select-remove-insert restart procedure is activated to diversify the search space whenever necessary. A waterborne ITT network in the port of Rotterdam is considered. Comprehensive simulations based on realistic ITT dataset are run to demonstrate the effectiveness of the proposed dynamic scheduling strategy. This work could be readily used to build towards a fully autonomous waterborne ITT system. Insights that support long term strategical decisions, such as the fleet size, could also be gained from the simulations.
The increasing ship size growth and land-based capacity restrictions at container terminals increase the need for optimization approaches in the process design of container ports. Several strategies can be found in the literature, ranging from the optimization of terminal processes to the introduction of truck appointment systems and the direct handling of ransshipment containers. In this paper, a possibility for process redesign of waterside container handling to external trucks is analysed. For this purpose, the impact of direct waterside container handling on the terminal is analysed using a discrete vent-based simulation model. The study shows that the approach for new process design has potential, although implementation is not easy.
Purpose
Since the first automated container terminal (ACT) was introduced at Europe Container Terminals Delta Terminal in Port Rotterdam back in the year 1992, a lot of research had been done to improve the management of ACT. However, up until recently, the number of literature available still appeared scarce. Hence, this paper aims to review the collection of literature about ACT to generate an exhaustive summary to answer the formulated review question in this study.
Design/methodology/approach
Preferred reporting items for systematic reviews and meta-analyses to narrow down the search parameters of literature retrieved so that only relevant articles were only selected. The systematic literature reviews were applied to analyse the content of the articles retrieved to determine its journal ranking, research findings and timeline of publications.
Findings
The adoption of ACT technology by container terminal operators could increase the terminal efficiency in productivity, cost reduction and environmental sustainability. Owing to global environmental awareness, the research trend of container terminal field and container terminal operator in the terminal design is much more environmentally friendly oriented.
Research limitations/implications
The limited numbers of experts in the management of ACT are causing challenges in data collections.
Practical implications
The analysis of the global ACT trend could help academicians and industrial investors to review the revolution timeline of maritime technology in port and shipping that is happening rapidly.
Originality/value
The analysis of timeline and collective literature leads to the propose of the conceptual framework to determine the relationship between increased productivity, cost reduction and environmentally sustainable.
With the significant growth of world economy and container transportation, large seaports are under the pressure of higher requirements for handling efficiency and often involved in recurrent congestion. For those large seaports, shuttle vessels are usually run between terminals in order to fulfill container inter-terminal transshipment demand as well as to alleviate seaports' congestion effectively. This paper focuses on planning the shuttle vessel routing and scheduling, in which shuttle vessels connect a main terminal and neighboring terminals for container pickup. Two mixed-integer programming formulations are developed. The first model aims to minimize the total operational cost and the second further takes into account the time window requirement. A two-phase heuristic algorithm is devised to find a near-optimal solution within the short computational time for large-scale problems. According to the computational results, the first model shows high searching efficiency if cargo owners do not have time requirement. The two-phase heuristic algorithm shows both efficiency and effectiveness in searching near-optimal solution of the second model for large-scale instances considering time windows. The routing analysis indicates that terminal operators focus on time or no-load rate, respectively, when the waiting penalty shift from low to high.
Global supply chains drive international trade growth, imposing challenges upon port operations. To cope with rising volumes, involved participants in port logistics systems must adopt a coordinated and streamlined operational decision-making. Along with suitable infrastructure, the proper deployment of smart concepts and technologies can improve port-hinterland connection. In this context, this paper aims to propose a smart port-hinterland integration concept, which allows for vehicle flow operational visibility and synchronisation. The concept is assessed considering real-world data obtained from five major Brazilian ports, which aimed to mitigate infrastructure challenges. Obtained results substantiate that the adoption of smart port logistics systems improves the efficiency and reliability of port-hinterland integration, reducing disruptions risks for involved global supply chains.
This paper addresses the joint vehicle dispatching and storage allocation problem in automated container terminals (ACTs). Two types of popular vehicles used in ACTs are considered in this problem: automated lifting vehicles (ALVs) and automated guided vehicles (AGVs). Two mixed-integer linear programming (MILP) models are proposed for the two types of vehicles, with the goal of minimizing the vehicle operating costs. To solve these models, this study develops a three-stage decomposition approach called particle swarm optimization, based on greedy search. Numerical experiments verify the applicability of the proposed models and the efficiency of the proposed algorithm. The study provides an effective vehicle management tool for terminal managers to handle vehicle dispatches in daily operations.
To increase efficiency and productivity of production and intralogistic facilities, automated transportation systems are widely used nowadays. This paper examines effects of interruptions in different transportation systems on the performance of production and intralogistic facilities by evaluating current literature with a focus on simulation-based studies. Our first contribution is a new categorisation of conveyor-based and vehicle-based transportation systems. This categorisation does not follow a technological differentiation but focuses on the abilities of the transportation system categories to deal with transportation system interruptions. Thereafter, current literature in the domains of 'manufacturing systems', 'semiconductor facilities', 'general intralogistics' (e.g., warehouses), and 'container terminals' is surveyed with respect to this categorisation. This survey is our second contribution and aims to identify research directions thus far not sufficiently considered. Finally, having surveyed different domains, the strengths and weaknesses of different transportation system categories are extracted from the literature and summarised. That summary is our final contribution, and is intended as a guideline and support for engineers planning transportation systems. Two main shortcomings in the current literature are identified: Firstly, although recognised as significantly influencing the facility's performance, transportation interruptions are not sufficiently considered. Secondly, relatively few simulation studies compare different categories of transportation systems.
This Chapter presents how to realize in WSN networks energy awareness spatial routing employing relations. Considering the routing issue in WSN networks we looked for such a solution that will allow defining the strategy for a global network operation without giving detailed, explicit orders that can interfere with nodes local activities. As the result of research carried out, we proposed novel approach using the relationships. This approach allows for the routing area sizing and implementation costs allocation for a number of nodes in a network.
We propose a novel semiopen queuing network (SOQN) model for the interterminal transportation (ITT) problem where multiple container terminals use a common fleet of vehicles (automated lift vehicles, automated guided vehicles, multitrailers, and barges) to transport containers between terminals. To solve the overall queuing network, our solution approach uses a network decomposition method where the original SOQN is decomposed to a closed and an open queuing network (with bulk-service capacity). To our knowledge, this is the first work that considers bulk service in SOQNs. We develop theoretical upper and lower bounds on the throughput time estimates of our model, and provide an extension for the case when service times at the terminal handling stations depend on the number of containers being loaded/unloaded. We numerically validate our model using simulated data where we find that our model results in errors of less than 5% for vehicle utilization. We also show that our model results in better estimates for the ITT problem when compared to existing approaches in the literature. Finally, we apply our model to real-world data from the Port of Rotterdam and show that it can be used to analyze throughput time trade-offs with alternate dwell point policies, different vehicle types, and variable vehicle capacities.
The online appendix is available at https://doi.org/10.1287/trsc.2016.0726 .
This paper addresses two coordination problems that exist in the waterborne transport in large seaports, the long time of stay of inland vessels and insufficient terminal and quay crane planning with respect to their sailing schedules. A novel coordination model is proposed and tackled using logic-based Benders decomposition and Large Neighborhood Search. In addition, a closed-loop perspective is taken, in which possible disturbances that may occur are considered. Simulation results show that our approach can scale to real-world sizes and provide better schedules for inland vessels within the port. The potential of using inland vessels for inter-terminal transport is also extensively investigated.
The design of automated RMGC systems plays a major role for the competitiveness of the container-storage yards and seaport container terminals as a whole. In this chapter, the strategical design-planning of automated RMGC systems is addressed in detail. It is started with a description of that planning problem, including a classification of decisions to be made, a discussion on objectives to be aimed at and an overview on parameters to be considered. Thereafter, an extensive review of the literature relevant to the problem of designing container-storage yards at seaport container terminals is provided. In particular, it is focused on the research approach used and the most important findings of the papers discussed. Based on the findings of the literature review, different types of general research approaches are introduced and discussed with respect to their applicability for the RMGC-design-planning problem.
As the actual decoupling point between maritime and inland transport, seaport container terminals play an essential role in the international container transport network, which is at the same time one of the greatest drivers and one of the greatest profiteers of the globalisation. In this chapter, the basic terms, facts and problems of seaport container terminals are introduced in order to prepare the ground for all following analyses. After a brief introduction of the container logistics sector as a whole, functions, operations and equipment types of container terminals are described, which is followed by definitions of several design and performance indicators for container terminals. Finally, a comprehensive overview on all kinds of planning problems arising at seaport container terminals is provided.
In the last four decades the container as an essential part of a unit-load-concept has achieved undoubted importance in international sea freight transportation. With ever increasing containerization the number of seaport container terminals and competition among them have become quite remarkable. Operations are nowadays unthinkable without effective and efficient use of information technology as well as appropriate optimization (operations research) methods. In this paper we describe and classify the main logistics processes and operations in container terminals and present a survey of methods for their optimization.
Thesis (Ph. D)--Erasmus Universiteit Rotterdam, 2005. TRAIL (Netherlands Research School for Transport, Infrastructure and Logistics) is a joint postgraduate Research School of the Delft University of Technology, Erasmus University Rotterdam, and the University of Groningen. Includes bibliographical references (p. [165]-173).
Significant unproductive and costly waiting occurs during AGV (Automated Guided Vehicle) use, both under the CC (Container Crane) and in the blocks compared to that of a manual yard tractor. A possible solution to this problem is that, in the design of ACT (Automated Container Terminals), ALV (Automated Lifting Vehicles), which can load and unload their own containers, be considered as an alternative. In this paper, the objective is to analyze how increases in the use of ALVs rather than AGVs affects the productivity of ACTs. We derived four inferences regarding the cycle time of vehicles and verified their validity in a simulation. A simulation model of an ACT with perpendicular layout was developed and is described in this paper. From the results of the simulation analysis, we determined the savings effect by cycle time and the required number of vehicles. We demonstrated that the ALV is superior to the AGV in both productivity and efficiency principally because the ALV eliminates the waiting time in the buffer zone.
At automated container terminals, containers are transshipped from one mode of transportation to another. Automated vehicles transport containers from the stack to the ship and vice versa. Two different types of automated vehicles are studied in this paper, namely automated lifting vehicles and automated guided vehicles. An automated lifting vehicle is capable of lifting a container from the ground by itself. An automated guided vehicles needs a crane to receive and deliver a container.
In designing automated container terminals one have to consider the choice for a certain type of equipment. The choice for a certain type of equipment should be made by performing a feasibility and economic analysis on various types of equipment. In this paper, we examine effects of using automated guided vehicles and automated lifting vehicles on unloading times of a ship, with simulation studies. In choosing a certain type of equipment we have considered criteria such as unloading times of a ship, occupancy degrees and the number of vehicles required. 38% more AGVs need to be used than ALVs. From this specific study, we conclude that, by observing only purchasing costs of equipment, ALVs are a cheaper option than AGVs.
To obtain an accurate analysis we have performed a sensitivity analysis. It can be concluded that the design of the terminal and technical aspects of quay cranes impact the number of vehicles required and as a result the choice for a certain type of equipment.
This paper presents a review on design and control of automated guided vehicle systems. We address most key related issues including guide-path design, determining vehicle requirements, vehicle scheduling, idle-vehicle positioning, battery management, vehicle routing and deadlock resolution. We discuss and classify important models and results from key publications in literature, including often-neglected areas, such as idle-vehicle positioning and battery management. In addition, we propose a new dispatching-rule classification, a framework for design and control of automated guided vehicle systems, and suggest some fruitful research directions.
The explosive growth in the freight volumes has put a lot of pressure on seaport authorities to find better ways of doing daily operations in order to improve the performance and to cope with avalanches of containers processing at container terminals. Advanced technologies, and in particular automated guided vehicle systems (AGVS), have been recently proposed as possible candidates for improving the terminal’s efficiency not only due to their abilities of significantly improving the performance but also to the repetitive nature of operations in container terminals. The deployment of AGVS may not be as effective as expected if the container terminal suffers from a poor layout. In this paper, simulation models are developed and used to demonstrate the impact of automation and terminal layout on terminal performance. In particular, two terminals with different but commonly used yard configurations are considered for automation using AGVS. A multi attribute decision making (MADM) method is used to assess the performance of the two terminals and determine the optimal number of deployed automated guided vehicles (AGVs) in each terminal. The simulation results demonstrate that substantial performance can be gained using AGVS. Furthermore, the yard layout has an effect on the number of AGVs used and on performance.
Intermodal terminals are important facilities in the container transport network, providing an exchange of containers between road and rail transport. Numerous factors can affect throughput in such highly integrated systems. These include numbers and types of equipment, physical layout, storage capacity and operating strategies. This study aims to improve operating strategies by developing an analytical tool to assist in load planning of container trains. The problem investigated can be described as a dynamic assignment problem with many uncertain parameters. Numerical investigations focus on tuning the proposed model to deal with the uncertainties.
Because a large number of vehicles use the same infrastructural facilities, the control of automated guided vehicle (AGV) traffic at a container terminal is crucial to the system performance. A new modelling technique which has been used to successfully model the relevant aspects of traffic control is presented in this paper. The control can be imposed by using a hierarchical system of so called semaphores, thus it is possible to follow a structural approach in the design of a traffic control configuration. The technique has been used to model an elementary terminal configuration and tested in a simulation model.
Due to the boom in world trade, port authorities are looking into
ways of making existing facilities more efficient. One way to improve
efficiency, increase capacity, and meet future demand is to use advanced
technologies and automation in order to speed up terminal operations. In
this paper, we design, analyze, and evaluate four different automated
container terminal (ACT) concepts. These concepts include automated
container terminals based on the use of automated guidance vehicles
(AGVs), a linear motor conveyance system (LMCS), an overhead grid rail
system (GR), and a high-rise automated storage and retrieval structure
(AS/RS). We use future demand scenarios to design the characteristics of
each terminal in terms of configuration, equipment and operations. A
microscopic simulation model is developed and used to simulate each
terminal system for the same operational scenario and evaluate its
performance. A cost model is used to evaluate the cost associated with
each terminal concept. Our results indicate that automation could
improve the performance of conventional terminals substantially and at a
much lower cost. Among the four concepts considered the one based on
automated guidance vehicles is found to be the most effective in terms
of performance and cost
Starting points; Phase 2: Architecture integrating information system
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- Hp Celen
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FAMAS—NewCon: Phase 1: Starting points; Phase 2: Architecture integrating information system, CTT publicatiereeks 32 An assignment model for dynamic load planning of intermodal trains
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- Ham Rth Van Der
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- Lindeijer Dg
- Meersmans R Pjm Dekker
- Koster Mbm De
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- Der
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Celen HP, Slegtenhorst RJW, Ham RTh van der, Nagel A, Berg J van den, Vos Burchart R de, Evers JJM, Lindeijer DG, Dekker R, Meersmans PJM, Koster MBM de, Meer R van der, Carlebur AFC, Nooijen FJAM (1999) FAMAS—NewCon: Phase 1: Starting points; Phase 2: Architecture integrating information system, CTT publicatiereeks 32 (in Dutch) Corry P, Kozan E (2006) An assignment model for dynamic load planning of intermodal trains. Comput Oper Res 33:1–17
Position paper, RSC-Rotterdam, Rotterdam Incomaas Report definition phase. Rotterdam (in Dutch Planning of inter terminal transport at the Maasvlakte. Working paper Intelligent control of vehicle-based internal transport systems A review of design and control of automated guided vehicle systems
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JJM, Koppers SAJ (1996) Automated guided vehicle traffic control at a container terminal. Transp Res A 30(1):21–34 Hoenders CGA (1994) Position paper, RSC-Rotterdam, Rotterdam Incomaas (1994) Report definition phase. Rotterdam (in Dutch) Kurstjens STGL, Dekker R, Dellaert NP, Duinkerken MB, Ottjes JA, Evers JJM (1996) Planning of inter terminal transport at the Maasvlakte. Working paper. TRAIL Research School, Delft Le Anh T (2005) Intelligent control of vehicle-based internal transport systems. Ph.D. Thesis, Erasmus University Rotterdam Le Anh T, de Koster MBM (2006) A review of design and control of automated guided vehicle systems. Eur J Oper Res 171(1):1–23
Verkenning operationele inzetbaarheid van een IT-hefvoertuig. TRAIL Onderzoekschool, Delft (in Dutch) MUST (1992) Simulation software Upward systems, The Netherlands Steenken D Container terminal operation and operations research—a classification and literature review
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KP, Evers JJM (1994) Verkenning operationele inzetbaarheid van een IT-hefvoertuig. TRAIL Onderzoekschool, Delft (in Dutch) MUST (1992) Simulation software. Upward systems, The Netherlands Steenken D, Voss S, Stahlbock R (2004) Container terminal operation and operations research—a classification and literature review. OR Spectrum 26:3–49
Simulation-based performance evaluation of transport vehicles at automated container terminals Theory of modelling and simulation
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CH, Choi YS, Ha TY (2004) Simulation-based performance evaluation of transport vehicles at automated container terminals. OR Spectrum 26:149–170 Zeigler BP, Praehofer H, Kim TG (2000) Theory of modelling and simulation, 2nd edn.
FAMAS—NewCon: Phase 1: Starting points; Phase 2: Architecture integrating information system
- Hp Celen
- Rjw Slegtenhorst
- Ham Rth Van Der
- A Nagel
- J Berg
- Vos Van Den
- R Burchart
- De
- Jjm Evers
- Dg Lindeijer
- R Dekker
- Pjm Meersmans
- Mbm Koster
- De
- Meer R Van Der
- Afc Carlebur
Position paper, RSC-Rotterdam
- Cga Hoenders
Planning of inter terminal transport at the Maasvlakte. Working paper
- Stgl Kurstjens
- R Dekker
- Np Dellaert
- Mb Duinkerken
- Ja Ottjes
- Jjm Evers
Verkenning operationele inzetbaarheid van een IT-hefvoertuig
- K P Meeusen
- Jjm Evers
- KP Meeusen
Meeusen KP, Evers JJM (1994) Verkenning operationele inzetbaarheid van een IT-hefvoertuig.
TRAIL Onderzoekschool, Delft (in Dutch)
FAMAS-NewCon: Phase 1: Starting points; Phase 2: Architecture integrating information system
- H P Celen
- Rjw Slegtenhorst
- Ham Rth Van Der
- A Nagel
- Vos Berg J Van Den
- Burchart R De
- Jjm Evers
- D G Lindeijer
- R Dekker
- Pjm Meersmans
- Mbm Koster
- De
- Meer R Van Der
- Afc Carlebur
- Fjam Nooijen
Celen HP, Slegtenhorst RJW, Ham RTh van der, Nagel A, Berg J van den, Vos Burchart R de,
Evers JJM, Lindeijer DG, Dekker R, Meersmans PJM, Koster MBM de, Meer R van der,
Carlebur AFC, Nooijen FJAM (1999) FAMAS-NewCon: Phase 1: Starting points; Phase 2:
Architecture integrating information system, CTT publicatiereeks 32 (in Dutch)