A method for generating a well-distributed Pareto set in nonlinear multiobjective optimization

S. V. Utyuzhnikov, P. Fantini, M. D. Guenov

Research output: Contribution to journalArticlepeer-review

52 Citations (Scopus)

Abstract

A method is presented for generating a well-distributed Pareto set in nonlinear multiobjective optimization. The approach shares conceptual similarity with the Physical Programming-based method, the Normal-Boundary Intersection and the Normal Constraint methods, in its systematic approach investigating the objective space in order to obtain a well-distributed Pareto set. The proposed approach is based on the generalization of the class functions which allows the orientation of the search domain to be conducted in the objective space. It is shown that the proposed modification allows the method to generate an even representation of the entire Pareto surface. The generation is performed for both convex and nonconvex Pareto frontiers. A simple algorithm has been proposed to remove local Pareto solutions. The suggested approach has been verified by several test cases, including the generation of both convex and concave Pareto frontiers.

Original languageEnglish
Pages (from-to)820-841
Number of pages22
JournalJournal of Computational and Applied Mathematics
Volume223
Issue number2
DOIs
Publication statusPublished - 15 Jan 2009
Externally publishedYes

Keywords

  • Multiobjective optimization
  • Pareto set
  • Pareto solution
  • Physical programming

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