Fuzzy set theory in medical diagnosis
IEEE Transactions on Systems, Man and Cybernetics
Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
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
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Truth-qualification and fuzzy relations in natural languages, application to medical diagnosis
Fuzzy Sets and Systems - Special issue dedicated to the memory of Professor Arnold Kaufmann
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 Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Fuzzy relation equations for coding/decoding processes of images and videos
Information Sciences—Informatics and Computer Science: An International Journal
A model for the prediction of “diseases” of firms by means of fuzzy relations
Fuzzy Sets and Systems
On the relation between equations with max-product composition and the covering problem
Fuzzy Sets and Systems
Fuzzy relation equations and fuzzy inference systems: an insideapproach
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An accelerated approach for solving fuzzy relation equations with a linear objective function
IEEE Transactions on Fuzzy Systems
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An optimization model with a linear objective function subject to max-t fuzzy relation equations as constraints is presented, where t is an Archimedean t-norm. Since the non-empty solution set of the fuzzy relation equations is in general a non-convex set, conventional linear programming methods are not suitable for solving such problems. The concept of covering problem is applied to establish 0-1 integer programming problem equivalent to linear programming problem and a binary coded genetic algorithm is proposed to obtain the optimal solution. An example is given for illustration of the method.