1984-2004 – 20 years of multiobjective metaheuristics. but what about the solution of combinatorial problems with multiple objectives?

  • Authors:

  • Xavier Gandibleux;Matthias Ehrgott

  • Affiliations:

  • LINA – FRE CNRS 2729, Université de Nantes, Nantes Cedex 03, France;Department of Engineering Science, The University of Auckland, Auckland, New Zealand

  • Venue:
  • EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
  • Year:
  • 2005

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Abstract

After 20 years of development of multiobjective metaheuristics the procedures for solving multiple objective combinatorial optimization problems are generally the result of a blend of evolutionary, neighborhood search, and problem dependent components. Indeed, even though the first procedures were direct adaptations of single objective metaheuristics inspired by evolutionary algorithms or neighborhood search algorithms, hybrid procedures have been introduced very quickly. This paper discusses hybridations found in the literature and mentions recently introduced metaheuristic principles.