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Journal Articles Journal of Heuristics Year : 2012

The efficiency of indicator-based local search for multi-objective combinatorial optimisation problems

Abstract

In the last few years, a significant number of multi-objective metaheuristics have been proposed in the literature in order to address real-world problems. Local search methods play a major role in many of these metaheuristic procedures. In this paper, we adapt a recent and popular indicator-based selection method proposed by Zitzler and Künzli in 2004, in order to define a population-based multi-objective local search. The proposed algorithm is designed in order to be easily adaptable, parameter independent and to have a high convergence rate. In order to evaluate the capacity of our algorithm to reach these goals, a large part of the paper is dedicated to experiments. Three combinatorial optimisation problems are tested: a flow shop problem, a ring star problem and a nurse scheduling problem. The experiments show that our algorithm can be applied with success to different types of multi-objective optimisation problems and that it outperforms some classical metaheuristics. Furthermore, the parameter sensitivity analysis enables us to provide some useful guidelines about how to set the parameters.
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Dates and versions

hal-00609252 , version 1 (04-05-2023)
hal-00609252 , version 2 (05-05-2023)

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Matthieu Basseur, Arnaud Liefooghe, Le Khoi, Edmund K. Burke. The efficiency of indicator-based local search for multi-objective combinatorial optimisation problems. Journal of Heuristics, 2012, 18 (2), pp.263-296. ⟨10.1007/s10732-011-9178-y⟩. ⟨hal-00609252v2⟩
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