A Spatiotemporal Partitioning Approach for Large-Scale Vehicle Routing Problems with Time Windows

For vehicle routing problems (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. The authors 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.

• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S1366554511000846
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13665545
• Supplemental Notes:
  • Abstract reprinted with permission from Elsevier
• Authors:
  • Qi, Mingyao
  • Lin, Wei-Hua
  • Li, Nan
  • Miao, Lixin
• Publication Date: 2012-1

Language

• English

Media Info

• Media Type: Web
• Features: Illustrations; References; Tables;
• Pagination: pp 248-257
• Serial:
  • Transportation Research Part E: Logistics and Transportation Review
  • Volume: 48
  • Issue Number: 1
  • Publisher: Elsevier
  • ISSN: 1366-5545
  • Serial URL: http://www.sciencedirect.com/science/journal/13665545

Subject/Index Terms

• TRT Terms: Cluster analysis; Genetic algorithms; Logistics; Numerical analysis; Routing; Time windows
• Uncontrolled Terms: Spatiotemporal analysis; Vehicle routing problem
• Subject Areas: Freight Transportation; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01359884
• Record Type: Publication
• Files: TRIS
• Created Date: Dec 30 2011 11:13AM