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Dynamic Delivery Plan Adaptation in Open Systems
Abstract
Open fleets offer a dynamic environment where the fleet is continually rebuilt ad-hoc since vehicles can enter or leave the fleet anytime, and the only immutable entity is the item to be delivered. Therefore, we need to be able to define a changeable delivery plan capable of adapting to such a dynamic environment. Hence, we propose Open Fleet Management, a Self-Management platform capable of optimizing plan delivery dynamically. The platform utilizes information about location, routes, delivery in transit and delivery costs to change the shipment plan according to the available carrier. Therefore, if two carriers are doing a shipment service to the same place, the platform will be able to discover such a situation and put them in contact to optimize the efficiency of the shipment.
Due to e-commerce growth and urbanization, delivery companies are facing a rising demand for home deliveries, which makes it increasingly challenging to provide parcel delivery that is cheap, sustainable, and on time. This challenge has motivated recent interest in crowdshipping. In crowdshipping systems, private citizens are incentivized to contribute to parcel delivery by making small detours in their daily lives. To advance crowdshipping as a new delivery paradigm, new crowdshipping concepts have to be developed, tested, and evaluated. One way to test and evaluate new crowdshipping concepts is agent-based simulation. In this paper, we present a crowdshipping simulator where the crowd workers are modeled as agents who decide autonomously whether they want to accept a delivery task. The agents’ decisions can be modeled based on shipping plans, which allow to easily implement the most common behavior assumptions found in the crowdshipping literature. We perform simulation experiments for different scenarios, which demonstrate the capabilities of our simulator.
This expanded and revised fourth edition of The Geography of Transport Systems provides a comprehensive and accessible introduction to the field with a broad overview of its concepts, methods and areas of application. Aimed mainly at an undergraduate audience, it provides an overview of the spatial aspects of transportation and focuses on how the mobility of passengers and freight is linked with geography. The book is divided in ten chapters, each covering a specific conceptual dimension, including networks, modes, terminals, freight transportation, urban transportation and environmental impacts, and updated with the latest information available. The fourth edition offers new material on the issues of transport and the economy, city logistics, supply chains, security, energy, the environment, as well as a revised content structure. With over 160 updated photographs, figures and maps, The Geography of Transport Systems presents transportation systems at different scales ranging from global to local and focuses on different contexts such as North America, Europe and East Asia. This volume is an essential resource for undergraduates studying transport geography, as well as those interested in economic and urban geography, transport planning and engineering. A companion web site, which contains additional material, has been developed for the book and can be found here: http://people.hofstra.edu/geotrans/.
The Vehicle Routing Problem (VRP) is a flourishing research area with clear applications to real-life distribution companies. However, most VRPrelated academic articles assume the existence of a homogeneous fleet of vehicles and/or a symmetric cost matrix. These assumptions are not always reasonable in real-life scenarios. To contribute closing this gap between theory and practice, we
propose a hybrid methodology for solving the Asymmetric and Heterogeneous Vehicle Routing Problem (AHVRP). In our approach we consider: (i) different types of vehicle loading capacities (heterogeneous fleets), and (ii) asymmetric distance-based costs. The proposed approach combines a randomized version of a well-known savings heuristic with several local searches specifically adapted to deal with the asymmetric nature of costs.Acomputational experiment allows us to discuss the efficiency of our approach and also to analyze how routing costs vary when slight departures from the homogeneous fleet assumption are considered.
In this paper we address several constrained transportation optimization problems (e.g. vehicle routing, shortest Hamiltonian path), for which we present novel algorithmic solutions and extensions, considering several optimization objectives, like minimizing costs and resource usage. All the considered problems are motivated by practical situations arising, for instance, in the mining and metallurgical industry or in data communication. We restrict our attention to transportation networks with path, tree or geometric structures, for which the developed polynomial-time algorithms are optimal or nearly optimal.
Nowadays, transportation is a critical sector of our lives, not only for the movement of people, but also to be capable to move goods around the world. Although providing such services can be seen as a very tiny problem in our society, behind it, there is a complex sector that requires sophisticated models and specific software to analyse a vast amount of information coming from different sources in order to provide a sustainable and efficient service. Given such a complex field, various issues have come up like the search of optimised routes, efficient assignment of vehicles, reduction of gas emissions, cost optimization problems, etc. In most cases, the provided approaches are focused on addressing the optimization problem considering fleets with identical features. In this work, we present HVSRec, a heterogeneous fleet semantic recommender system that integrates mechanisms to manage vehicles of different nature and characteristics efficiently. The platform is aimed to connect customers that request a transportation of a certain good with drivers that are offering transportation services with their own vehicle.
Nowadays, vehicles of modern fleets are endowed with advanced devices that allow the operators of a control center to have global knowledge about fleet status, including existing incidents. Fleet management systems support real-time decision making at the control center so as to maximize fleet performance. In this paper, setting out from our experience in dynamic coordination of fleet management systems, we focus on fleets that are open, dynamic and highly autonomous. Furthermore, we propose how to cope with the scalability problem as the number of vehicles grows. We present our proposed architecture for open fleet management systems and use the case of taxi services as example of our approach. We carried out some experiments, which showed our proposed algorithm outperform the most common assignment method both in waiting times of clients and taxi costs.
China has been the second CO2 emitter in the world, while the transportation sector accounts for a major share of CO2 emissions. Analysis of transportation sector CO2 emissions is help to decrease CO2 emissions. Thus the purpose of this paper is to investigate the potential factors influencing the change of transport sector CO2 emissions in China. First, the transport sector CO2 emissions over the period 1985–2009 is calculated based on the presented method. Then the presented LMDI (logarithmic mean Divisia index) method is used to find the nature of the factors those influence the changes in transport sector CO2 emissions. We find that: (1) Transport sector CO2 emissions has increased from 79.67 Mt in 1985 to 887.34 Mt in 2009, following an annual growth rate of 10.56%. Highways transport is the biggest CO2 emitter. (2) The per capita economic activity effect and transportation modal shifting effect are found to be primarily responsible for driving transport sector CO2 emissions growth over the study period. (3) The transportation intensity effect and transportation services share effect are found to be the main drivers of the reduction of CO2 emissions in China. However, the emission coefficient effect plays a very minor role over the study period.
The mining and construction industries have used match factor for many decades as an indicator of productivity performance. The term match factor is usually defined as the ratio of truck arrival rate to loader service time. This ratio relies on the assumption that the truck and loader fleets are homogeneous. That is, all the trucks are of the same type, and all the loaders are of the same type. In reality, mixed fleets are common. This paper proposes a method of defining match factor for heterogeneous fleets: in particular, a heterogeneous trucking fleet, a heterogeneous loading fleet, and the case where both truck and loader fleets are heterogeneous.