Solving the vehicle routing problem with stochastic demands using the cross-entropy method

Krishna Chepuri, Tito Homem-De-Mello

Research output: Contribution to journalArticlepeer-review

129 Scopus citations

Abstract

An alternate formulation of the classical vehicle routing problem with stochastic demands (VRPSD) is considered. We propose a new heuristic method to solve the problem, based on the Cross-Entropy method. In order to better estimate the objective function at each point in the domain, we incorporate Monte Carlo sampling. This creates many practical issues, especially the decision as to when to draw new samples and how many samples to use. We also develop a framework for obtaining exact solutions and tight lower bounds for the problem under various conditions, which include specific families of demand distributions. This is used to assess the performance of the algorithm. Finally, numerical results are presented for various problem instances to illustrate the ideas.

Original languageEnglish
Pages (from-to)153-181
Number of pages29
JournalAnnals of Operations Research
Volume134
Issue number1
DOIs
StatePublished - Jan 2005
Externally publishedYes

Keywords

  • Cross-entropy method
  • Stochastic optimization
  • Vehicle routing problem

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