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Two-phase Pareto local search for the biobjective traveling salesman problem

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Abstract

In this work, we present a method, called Two-Phase Pareto Local Search, to find a good approximation of the efficient set of the biobjective traveling salesman problem. In the first phase of the method, an initial population composed of a good approximation of the extreme supported efficient solutions is generated. We use as second phase a Pareto Local Search method applied to each solution of the initial population. We show that using the combination of these two techniques: good initial population generation plus Pareto Local Search gives better results than state-of-the-art algorithms. Two other points are introduced: the notion of ideal set and a simple way to produce near-efficient solutions of multiobjective problems, by using an efficient single-objective solver with a data perturbation technique.

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Authors and Affiliations

  1. Faculté Polytechnique de Mons, Laboratory of Mathematics and Operational Research, Mons, Belgium

    Thibaut Lust & Jacques Teghem

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  1. Thibaut Lust
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  2. Jacques Teghem
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Correspondence to Thibaut Lust.

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T. Lust thanks the “Fonds National de la Recherche Scientifique” for a research fellow grant (Aspirant FNRS).

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Lust, T., Teghem, J. Two-phase Pareto local search for the biobjective traveling salesman problem. J Heuristics 16, 475–510 (2010). https://doi.org/10.1007/s10732-009-9103-9

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  • DOI: https://doi.org/10.1007/s10732-009-9103-9

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