Tabu-based GIS for solving the vehicle routing problem |
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| Affiliation: | 1. LARODEC, Institut Supérieur de Gestion, University of Tunis, Tunisia;2. Faculté des Sciences Juridiques, Economiques et de Gestion, University of Jendouba, Tunisia;3. LTSIRS, Ecole Nationale des Ingénieurs de Tunis, University of El Manar, Tunisia;4. Institut Supérieur des Arts Multimédia de la Manouba, University of Manouba, Tunisia;1. Instituto Superior Técnico, Universidade de Lisboa, Av. Prof. Dr. Aníbal Cavaco Silva, 2744-016 Porto Salvo, Portugal;2. INESC-ID Lisboa, Av. Prof. Dr. Aníbal Cavaco Silva, 2744-016 Porto Salvo, Portugal;1. Institute of Computing, University of Campinas, SP, Brazil;2. Dept. of Computer Engineering, Federal Technological University of Parana, PR, Brazil;3. IMMUNOCAMP Research and Development of Technology, SP, Brazil;4. Institute of Biology, University of Campinas, SP, Brazil;1. Department of Energy, Politecnico di Milano, via Ponzio 34/3, 20133 Milan, Italy;2. Systems Science and the Energetic Challenge, European Foundation for New Energy-Electricité de France, Ecole Centrale Paris and Supelec, Paris, 92295 Chatenay-Malabry Cedex, France;3. Faculty of Engineering and Computing, Coventry University, Priory Street, Coventry, UK;1. Institute for Development & Research in Banking Technology, Hyderabad, India;2. School of Computer & Information Science, University of Hyderabad, Hyderabad, India;1. Department of Computer Architecture and Technology, University of the Basque Country UPV/EHU, Donostia-San Sebastian 20018, Spain;2. Department of Computer Science and Artificial Intelligence, University of the Basque Country UPV/EHU, Donostia-San Sebastian 20018, Spain |
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| Abstract: | Besides being a hard combinatorial problem, the VRP is also a spatial problem. Hence, effective decision making in this field strongly requires the integration of GIS and optimization systems (GIS-O). This article integrates GIS and optimization tools for solving the vehicle routing problem with loading and distance requirements (DCVRP). A general outline of the multi-step integration is pointed out showing the interaction of the GIS and the spatial optimization according to the loose coupling strategy. The computational performance of the TS-VRP algorithm for the DCVRP turned out to be quite efficient on both computation time and solution quality. The Tunisian case study well illustrates the incentive behind using such a spatial decision support system that allows the management of the problem from the data acquisition to the visualization of possible simulation scenarios in a more realistic way. |
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| Keywords: | GIS SDSS Optimization Loose integration DCVRP Tabu search |
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