Optimization under Fuzzy Rule Constraints

Authors

  • C. Carlsson IAMSR, Åbo Akademi University
  • R. Fullér Department of OR, Eötvös Loránd University
  • S. Giove Department of Applied Mathematics, University of Venice

Abstract

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 is a linear combination of the crisp values of the decision variables. We suggest the use of Takagi and Sugeno fuzzy reasoning method to determine the crisp functional relationship between the objective function and the decision variables, and solve the resulting (usually non linear) programming problem to find a fair optimal solution to the original fuzzy problem. 

Downloads

Published

1998-09-01

How to Cite

Carlsson, C., Fullér, R., & Giove, S. (1998). Optimization under Fuzzy Rule Constraints. JORBEL - Belgian Journal of Operations Research, Statistics, and Computer Science, 38(2-3), 17–24. Retrieved from https://www.orbel.be/jorbel/index.php/jorbel/article/view/285

Issue

Section

Articles