A decision support system for cooperative transportation planning: Design,implementation, and performance assessment |
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| Affiliation: | 1. Faculty of Computer Science, Otto-von-Guericke University Magdeburg, Universitätsplatz 2, D-39106 Magdeburg, Germany;2. Institute for Community Medicine, Ernst-Moritz-Arndt University Greifswald, Walther-Rathenau-Straße 48, D-17475 Greifswald, Germany;3. Institute for Diagnostic Radiology and Neuroradiology, Ernst-Moritz-Arndt University Greifswald, Sauerbruchstraße, D-17487 Greifswald, Germany;1. Computer Science Department, Federal University of Maranhão (UFMA), São Luís, MA, Brazil;2. Department of Informatics, University of Minho, Braga, Portugal;1. University of Pannonia, Department of Process Engineering, P.O. Box 158, Veszpreém H-8200, Hungary;2. The Finnish Microarray and Sequencing Centre, Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Tykistökatu 6A, 20520 Turku, Finland;1. Khalifa University of Science, Technology and Research, P.O. Box 127788, Abu Dhabi, United Arab Emirates;2. Etisalat BT Innovation Center, P.O. Box 127788, Abu Dhabi, United Arab Emirates;1. Department of Informatics, Universidad Técnica Federico Santa María, Avenida España 1680, Valparaíso, Chile;2. Intelligent Systems Laboratory, University of Bristol, MVB, Woodland Rd, Bristol, BS8 1UB, UK |
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| Abstract: | In this paper, we describe a decision support system for cooperative transportation planning in the German food industry where several manufacturing companies share their fleets to reduce transportation costs. Besides using vehicles of their fleets, there are different outsourcing options offered by logistics service providers, but these are much more expensive. The decision-making kernel of the decision support system is implemented as a multi-agent-system (MAS). The kernel provides a distributed hierarchical algorithm for cooperative transportation planning and an on-line data layer that contains all the information for decision making. We sketch the distributed hierarchical transportation planning algorithm and identity the required software agents. The MAS interacts via web services with a commercial tour planning system that persistently stores the resulting tour plans, orders, and customer data. Moreover, the tour planning system is used to offer graphical user interfaces to interact with the users. The data layer is updated by order and customer data from the ERP systems of the different manufacturing companies. We describe the architecture and the implementation of the MAS and the overall coupling framework. Furthermore, we discuss the simulation-based performance assessment of the resulting decision support system when the system is applied in a rolling horizon setting and present some computational results. The results demonstrate that the MAS approach is appropriate for the cooperative transportation planning domain. |
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| Keywords: | Cooperative transportation planning Multi-agent-systems Integration Simulation-based performance assessment |
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