A Method for Selecting Pareto Optimal Solutions in Multiobjective Optimization

Authors

  • Mohamed Cheikh GIAD, FSEGS, route de l'aéroport km 4 Sfax 3018, Tunisie
  • Bassem Jarboui GIAD, FSEGS, route de l'aéroport km 4 Sfax 3018, Tunisie
  • Taí¯cir Loukil LOGIQ, ISGIS, route Mharza Km 1.5 BP. 954, Sfax 3018, Tunisie
  • Patrick Siarry Lissi, université de Paris 12, 61av. du Général de Gaulle, 94010 Créteil, France

DOI:

https://doi.org/10.26713/jims.v2i1.27

Keywords:

Partitional clustering, Hierarchical algorithms, Variable neighborhood search, Multicriteria analysis

Abstract

In many real-life multiobjective optimization problems and particularly in combinatorial ones, a common methodology is to determine a Pareto optimal set. These sets can be extremely large or may contain an infinite number of solutions. It is then difficult to choose among these solutions, one that corresponds to the best compromise according to the decision-maker's preferences. In this paper, we propose a model to select a restricted set of solutions. These sets should be structurally different and the most representative of the Pareto-optimal solutions. Our model is implemented using hierarchical algorithms and variable neighborhood search metaheuristics.

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CITATION

How to Cite

Cheikh, M., Jarboui, B., Loukil, T., & Siarry, P. (2010). A Method for Selecting Pareto Optimal Solutions in Multiobjective Optimization. Journal of Informatics and Mathematical Sciences, 2(1), 51–62. https://doi.org/10.26713/jims.v2i1.27

Issue

Vol. 2 No. 1 (2010)

Section

Research Articles

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