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A simple, deterministic, and efficient knowledge-driven heuristic for the vehicle routing problem

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  • ARNOLD, Florian
  • SÖRENSEN, Kenneth

Abstract

In this paper we develop a heuristic for the capacitated vehicle routing problem that revolves around three complementary local search operators, embedded in a guided local search framework. The efficiency of the operators is guaranteed by using knowledge, obtained through data mining, on the attributes of undesirable edges. In spite of its straightforward design and the fact that it is completely deterministic, the heuristic is competitive with the best heuristics in the literature in terms of accuracy and speed. Moreover, it can be readily extended to solve a wide range of vehicle routing problems, which we demonstrate by applying it to the multi-depot vehicle routing problem.

Suggested Citation

  • ARNOLD, Florian & SÖRENSEN, Kenneth, 2017. "A simple, deterministic, and efficient knowledge-driven heuristic for the vehicle routing problem," Working Papers 2017012, University of Antwerp, Faculty of Business and Economics.
    • Handle: RePEc:ant:wpaper:2017012
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    File URL: https://repository.uantwerpen.be/docman/irua/2c5812/147947.pdf
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    References listed on IDEAS

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    7. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2013. "Heuristics for multi-attribute vehicle routing problems: A survey and synthesis," European Journal of Operational Research, Elsevier, vol. 231(1), pages 1-21.
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    Keywords

    Vehicle routing problems; Heuristics; Metaheuristics;
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