Solving interval-valued fuzzy relation equations

Authors:
Guangzhi Li;Shu-Cherng Fang
Affiliations:
Dept. of Oper. Res. & Ind. Eng., North Carolina State Univ., Raleigh, NC;-
Venue:
IEEE Transactions on Fuzzy Systems
Year:
1998

Citing 0
Cited 8

Multi-objective optimization problems with fuzzy relation equation constraints

Fuzzy Sets and Systems - Special issue: Optimization and decision support systems
Solution Sets of Interval-Valued Min-S-Norm Fuzzy Relational Equations

Fuzzy Optimization and Decision Making
A note on solution sets of interval-valued fuzzy relational equations

Fuzzy Optimization and Decision Making
A survey on fuzzy relational equations, part I: classification and solvability

Fuzzy Optimization and Decision Making
Solving interval-valued fuzzy relation equations with a linear objective function (P2054)

FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 4
Thermal condition monitoring system using log-polar mapping, quaternion correlation and max-product fuzzy neural network classification

Neurocomputing
Complete solution sets of inf → interval-valued fuzzy relation equations

Information Sciences: an International Journal
An algorithm for solving optimization problems with fuzzy relational inequality constraints

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Solving systems of fuzzy relation equations is an important topic in fuzzy set theory. This paper studies the composite interval-valued fuzzy relation equations. After analyzing the properties of its solution set, we convert the fuzzy relation equations into a fuzzy relation inequality system and propose an efficient computational procedure to generate the whole solution set. Examples are included to illustrate the idea and algorithm