Highlights ► We solved a large-scale VRPTW based on spatiotemporal clustering on customers. ► We proposed a metric for characterizing spatiotemporal distance between customers. ► The method proposed has the potential to handle large-scale VRTPW.
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.
A spatiotemporal partitioning approach for large-scale vehicle routing problems with time windows
Transportation Research Part E: Logistics and Transportation Review ; 48 , 1 ; 248-257
2011-05-15
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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