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A tabu search heuristic using genetic diversification for the clustered traveling salesman problem

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Abstract

The clustered traveling salesman problem is an extension of the classical traveling salesman problem where the set of vertices is partitioned into clusters. The objective is to find a least cost Hamiltonian cycle such that the vertices of each cluster are visited contiguously and the clusters are visited in a prespecified order. A tabu search heuristic is proposed to solve this problem. This algorithm periodically restarts its search by merging two elite solutions to form a new starting solution (in a manner reminiscent of genetic algorithms). Computational results are reported on sets of Euclidean problems with different characteristics.

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Authors and Affiliations

  1. Centre de recherche sur les transports, Université de Montréal, succursale Centre-ville, C.P. 6128, H3C 3J7, Montréal, Québec, Canada

    Gilbert Laporte

  2. École des Hautes Études Commerciales, 5255, avenue Decelles, H3T 1V6, Montréal, Québec, Canada

    Gilbert Laporte

  3. Centre de recherche sur les transports, Université de Montréal, succursale Centre-ville, C.P. 6128, H3C 3J7, Québec, Montréal, Canada

    Jean-Yves Potvin

  4. Département d'informatique et de recherche opérationnelle, Université de Montréal, succursale Centreville, C.P. 6128, H3C 3J7, Montréal, Québec, Canada

    Jean-Yves Potvin

  5. Centre Universitaire des Sciences et Techniques, Université Blaise Pascal, 63174, Clermont-Ferrand, Aubière Cedex, France

    Florence Quilleret

Authors
  1. Gilbert Laporte
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  2. Jean-Yves Potvin
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  3. Florence Quilleret
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Laporte, G., Potvin, JY. & Quilleret, F. A tabu search heuristic using genetic diversification for the clustered traveling salesman problem. J Heuristics 2, 187–200 (1997). https://doi.org/10.1007/BF00127356

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