Fuzzy relation equations theory as a basis of fuzzy modelling: an overview
Fuzzy Sets and Systems - Special memorial volume on fuzzy logic and uncertainly modelling
Theory of T-norms and fuzzy inference methods
Fuzzy Sets and Systems - Special memorial volume on fuzzy logic and uncertainly modelling
Design of fuzzy logic controllers based on generalized T-operators
Fuzzy Sets and Systems - Special memorial volume on fuzzy logic and uncertainly modelling
s-t fuzzy relational equations
Fuzzy Sets and Systems
Solving fuzzy relation equations with a linear objective function
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
A Note on Fuzzy Relation Programming Problems with Max-Strict-t-Norm Composition
Fuzzy Optimization and Decision Making
On the relation between equations with max-product composition and the covering problem
Fuzzy Sets and Systems
An efficient solution procedure for fuzzy relation equations with max-product composition
IEEE Transactions on Fuzzy Systems
Latticized linear optimization on the unit interval
IEEE Transactions on Fuzzy Systems
Mathematical and Computer Modelling: An International Journal
Novel approximate solving algorithm for fuzzy relational equations
Mathematical and Computer Modelling: An International Journal
An algorithm for solving optimization problems with fuzzy relational inequality constraints
Information Sciences: an International Journal
Hi-index | 0.98 |
In this study we investigate the problem of minimizing an objective function with single-term exponents subject to fuzzy relational equations specified in max-min composition. Two folds are presented. First, we present some properties for this optimization problem under the assumption of both negative and nonnegative exponents in the objective function. Second, we provide an efficient procedure to solve this optimization problem without looking for all the potential minimal solutions. Two concrete examples are provided to illustrate the procedure.