کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1023747 | 941643 | 2012 | 10 صفحه PDF | دانلود رایگان |
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.
► 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.
Journal: Transportation Research Part E: Logistics and Transportation Review - Volume 48, Issue 1, January 2012, Pages 248–257