A spatiotemporal partitioning approach for large-scale vehicle routing problems with time windows

Mingyao Qi, Wei Hua Lin, Nan Li, Lixin Miao

Research output: Contribution to journalArticle

19 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)248-257
Number of pages10
JournalTransportation Research Part E: Logistics and Transportation Review
Volume48
Issue number1
DOIs
StatePublished - Jan 2012

Fingerprint

Vehicle routing
customer
Genetic algorithms
time
Time windows
Partitioning
Vehicle routing problem
Clustering

Keywords

  • Logistics
  • Spatiotemporal distance
  • Time geography
  • Vehicle routing with time windows

ASJC Scopus subject areas

  • Business and International Management
  • Management Science and Operations Research
  • Transportation

Cite this

A spatiotemporal partitioning approach for large-scale vehicle routing problems with time windows. / Qi, Mingyao; Lin, Wei Hua; Li, Nan; Miao, Lixin.

In: Transportation Research Part E: Logistics and Transportation Review, Vol. 48, No. 1, 01.2012, p. 248-257.

Research output: Contribution to journalArticle

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