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Probabilistic diversification and intensification in local search for vehicle routing

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Abstract

This article presents a probabilistic technique to diversify, intensify, and parallelize a local search adapted for solving vehicle routing problems. This technique may be applied to a very wide variety of vehicle routing problems and local searches. It is shown that efficient first-level tabu searches for vehicle routing problems may be significantly improved with this technique. Moreover, the solutions produced by this technique may often be improved by a postoptimization technique presented in this article, too. The solutions of nearly forty problem instances of the literature have been improved.

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Authors and Affiliations

  1. Department of Mathematics, École Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland

    Yves Rochat

  2. Center of Research on Transportation, Université de Montréal, succursale Centre-Ville, C.P. 6128, H3C 3J7, Montréal, Canada

    Éric D. Taillard

Authors
  1. Yves Rochat
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  2. Éric D. Taillard
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Rochat, Y., Taillard, É.D. Probabilistic diversification and intensification in local search for vehicle routing. J Heuristics 1, 147–167 (1995). https://doi.org/10.1007/BF02430370

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  • DOI: https://doi.org/10.1007/BF02430370

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