Solving fuzzy optimization problems by evolutionary algorithms

  • Authors:
  • F. Jiménez;J. M. Cadenas;J. L. Verdegay;G. Sánchez

  • Affiliations:
  • Department Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Espinardo, 30071 Murcia, Spain;Department Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Espinardo, 30071 Murcia, Spain;Department Ciencias de la Computación e Inteligencia Artificial, Universidad de Granada, 18071 Granada, Spain;Department Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Espinardo, 30071 Murcia, Spain

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2003

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Abstract

In this paper mathematical programming problems with fuzzy constraints are dealt with. Fuzzy solutions are obtained by means of a parametric approach in conjunction with evolutionary techniques. Some relevant characteristics of the evolutionary algorithm are for instance a real-coded representation of solutions and the preselection scheme as niche formation and elitist technique. Three test problems with fuzzy constraints and different structures are used in order to check and compare the proposed technique. The results obtained are very good in comparison with those from another methods.