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Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: The efficiency of indicator-based local search for multi-objective combinatorial optimisation problems
Author(s): Basseur, Matthieu
Liefooghe, Arnaud
Le, Khoi
Burke, Edmund
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Keywords: Multi-objective optimisation
Local search
Indicator-based optimisation
Flow-shop problem
Ring star problem
Nurse scheduling problem
Issue Date: Apr-2012
Citation: Basseur M, Liefooghe A, Le K & Burke E (2012) The efficiency of indicator-based local search for multi-objective combinatorial optimisation problems, Journal of Heuristics, 18 (2), pp. 263-296.
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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