A spatiotemporal partitioning approach for large-scale vehicle routing problems with time windows |
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Authors: | Mingyao QiWei-Hua Lin Nan LiLixin Miao |
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Institution: | a Research Center on Modern Logistics, Graduate School at Shenzhen, Tsinghua University, Shenzhen, 518055, China b Department of Systems and Industrial Engineering, The University of Arizona, Tucson, AZ 85721, USA |
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Abstract: | For VRP with time windows (VRPTW) solved by conventional cluster-first and route-second approach, temporal information is usually considered with vehicle routing but ignored in the process of clustering. We propose an alternative approach based on spatiotemporal partitioning to solving a large-scale VRPTW, considering jointly the temporal and spatial information for vehicle routing. A spatiotemporal representation for the VRPTW is presented that measures the spatiotemporal distance between two customers. The resulting formulation is then solved by a genetic algorithm developed for k-medoid clustering of large-scale customers based on the spatiotemporal distance. The proposed approach showed promise in handling large scale networks. |
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Keywords: | Vehicle routing with time windows Logistics Time geography Spatiotemporal distance |
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