New ideas in applying scatter search to multiobjective optimization

Authors:
Antonio J. Nebro;Francisco Luna;Enrique Alba
Affiliations:
Departamento de Lenguajes y Ciencias de la Computación, E.T.S. Ingeniería Informática, Málaga, Spain;Departamento de Lenguajes y Ciencias de la Computación, E.T.S. Ingeniería Informática, Málaga, Spain;Departamento de Lenguajes y Ciencias de la Computación, E.T.S. Ingeniería Informática, Málaga, Spain
Venue:
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Year:
2005

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Abstract

This paper elaborates on new ideas of a scatter search algorithm for solving multiobjective problems. Our approach adapts the well-known scatter search template for single objective optimization to the multiobjective field. The result is a simple and new metaheuristic called SSMO, which incorporates typical concepts from the multiobjective optimization domain such as Pareto dominance, crowding, and Pareto ranking. We evaluate SSMO with both constrained and unconstrained problems and compare it against NSGA-II. Preliminary results indicate that scatter search is a promising approach for multiobjective optimization.