Optimization under fuzzy if-then rules

Christer Carlsson, Robert Fullér

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

The aim of this paper is to introduce a novel statement of fuzzy mathematical programming problems and to provide a method for finding a fair solution to these problems. Suppose we are given a mathematical programming problem in which the functional relationship between the decision variables and the objective function is not completely known. Our knowledge-base consists of a block of fuzzy if-then rules, where the antecedent part of the rules contains some linguistic values of the decision variables, and the consequence part consists of a linguistic value of the objective function. We suggest the use of Tsukamoto's fuzzy reasoning method to determine the crisp functional relationship between the objective function and the decision variables, and solve the resulting (usually nonlinear) programming problem to find a fair optimal solution to the original fuzzy problem.

Original languageEnglish
Pages (from-to)111-120
Number of pages10
JournalFuzzy Sets and Systems
Volume119
Issue number1
DOIs
Publication statusPublished - Apr 1 2001

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Keywords

  • Fuzzy optimization
  • Linguistic variable
  • Soft constraints
  • Tsukamoto's fuzzy reasoning

ASJC Scopus subject areas

  • Logic
  • Artificial Intelligence

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