A Study on Dominance-Based Local Search Approaches for Multiobjective Combinatorial Optimization

Authors:
Arnaud Liefooghe;Salma Mesmoudi;Jérémie Humeau;Laetitia Jourdan;El-Ghazali Talbi
Affiliations:
Laboratoire d'Informatique Fondamentale de Lille, UMR CNRS 8022, INRIA Lille-Nord Europe, Université Lille 1, Villeneuve d'Ascq, France;Laboratoire d'Informatique Fondamentale de Lille, UMR CNRS 8022, INRIA Lille-Nord Europe, Université Lille 1, Villeneuve d'Ascq, France;Laboratoire d'Informatique Fondamentale de Lille, UMR CNRS 8022, INRIA Lille-Nord Europe, Université Lille 1, Villeneuve d'Ascq, France;Laboratoire d'Informatique Fondamentale de Lille, UMR CNRS 8022, INRIA Lille-Nord Europe, Université Lille 1, Villeneuve d'Ascq, France;Laboratoire d'Informatique Fondamentale de Lille, UMR CNRS 8022, INRIA Lille-Nord Europe, Université Lille 1, Villeneuve d'Ascq, France
Venue:
SLS '09 Proceedings of the Second International Workshop on Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics
Year:
2009

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Abstract

The purpose of the current paper is twofold. First, a unified view of dominance-based multiobjective local search algorithms is proposed. We focus on methods based on the iterative improvement of the nondominated set by means of a neighborhood operator. Next, the effect of current solutions selection and of neighborhood exploration techniques for such purpose is studied. Experiments are conducted on a permutation flowshop scheduling problem in a two- and a three-objective variant.