An interactive fuzzy satisficing approach using genetic algorithm for multi-objective problems

Takanori Kiyota, Yasutaka Tsuji, Eiji Kondo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper describes a fuzzy satisficing method for multi-objective optimization problems using Genetic Algorithm (GA). A multi-objective design problem with constraints is expressed as a satisficing problem of constraints by introducing an aspiration level for each objective. Here, in order to handle fuzziness involved in aspiration levels and constraints, the unsatisfying function is introduced, and the problem is formulated as a multi-objective minimization problem of unsatisfaction ratings. As the optimization method, GA is employed. He/She can seek a satisficing solution by modifying parameters interactively according to his/her preferences.

Original languageEnglish
Title of host publicationAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
EditorsM.H. Smith, W.A. Gruver, L.O. Hall
Pages757-762
Number of pages6
Volume2
Publication statusPublished - 2001
EventJoint 9th IFSA World Congress and 20th NAFIPS International Conference - Vancouver, BC, Canada
Duration: Jul 25 2001Jul 28 2001

Other

OtherJoint 9th IFSA World Congress and 20th NAFIPS International Conference
CountryCanada
CityVancouver, BC
Period7/25/017/28/01

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Media Technology

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