Sets of solution-set-invariant coefficient matrices of simple fuzzy relation equations
Fuzzy Sets and Systems
A computer algorithm for the solution of the inverse problem of fuzzy systems
Fuzzy Sets and Systems
The smallest solution of max-min fuzzy equations
Fuzzy Sets and Systems
A software routine to solve the generalized inverse problem of fuzzy systems
Fuzzy Sets and Systems
Fuzzy Sets and Systems
Some results on the resolution of fuzzy relation equations
Fuzzy Sets and Systems
On an algorithm for solving fuzzy linear systems
Fuzzy Sets and Systems
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
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
Multi-objective optimization problems with fuzzy relation equation constraints
Fuzzy Sets and Systems - Special issue: Optimization and decision support systems
An accelerated approach for solving fuzzy relation equations with a linear objective function
IEEE Transactions on Fuzzy Systems
Matrix-pattern-based computer algorithm for solving fuzzy relation equations
IEEE Transactions on Fuzzy Systems
Linear optimization with bipolar max-min constraints
Information Sciences: an International Journal
An algorithm for solving optimization problems with fuzzy relational inequality constraints
Information Sciences: an International Journal
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In this paper, we study the problem of minimizing a linear objective function subject to a fuzzy system constraint. By utilizing the fuzzy system's compact system, we define k-form chained solutions and spaces of k-form chained solutions. Then we prove that any minimal solution of the fuzzy system is a k-form chained solution. By using an operation method expressed in tables, we sieve out basic solutions from the spaces of k-form chained solutions. Finally, we obtain optimal solutions of the studied problem from the obtained basic solutions. Examples are provided to show that our algorithm is simple and convenient.