Fuzzy set theory in medical diagnosis
IEEE Transactions on Systems, Man and Cybernetics
Further contributions to the study of finite fuzzy relations equations
Fuzzy Sets and Systems
Design of fuzzy logic controllers based on generalized T-operators
Fuzzy Sets and Systems - Special memorial volume on fuzzy logic and uncertainly modelling
Processing in relational structures: fuzzy relational equations
Fuzzy Sets and Systems - Special memorial volume on foundations of fuzzy reasoning
Linear optimization and extensions: theory and algorithms
Linear optimization and extensions: theory and algorithms
Solution algorithms for fuzzy relational equations with max-product composition
Fuzzy Sets and Systems
Solving fuzzy relation equations with a linear objective function
Fuzzy Sets and Systems
Optimization of fuzzy relation equations with max-product composition
Fuzzy Sets and Systems
Solving nonlinear optimization problems with fuzzy relation equation constraints
Fuzzy Sets and Systems
Fuzzy Relation Equations and Their Applications to Knowledge Engineering
Fuzzy Relation Equations and Their Applications to Knowledge Engineering
Multi-objective optimization problems with fuzzy relation equation constraints
Fuzzy Sets and Systems - Special issue: Optimization and decision support systems
Fuzzy Optimization and Decision Making
Introduction to Mathematical Programming: Applications and Algorithms
Introduction to Mathematical Programming: Applications and Algorithms
Linear optimization with an arbitrary fuzzy relational inequality
Fuzzy Sets and Systems
Hi-index | 0.01 |
In this paper, we extend Guo and Xia's necessary condition which has been presented by Guo and Xia (Fuzzy optimizat Decis Mak 5: 33---47, 2006) in order to study the finitely many constraints of fuzzy relation inequalities and optimize a linear objective function on this region which is defined by the fuzzy max---min operator. The new condition provides a means for removing the unnecessary paths resulting from Guo and Xia's paths. Also, an algorithm and two numerical examples are offered to abbreviate and illustrate the steps of the resolution process of the problem.