Fuzzy Linear Programming models and methods has been one ofthe most and well studied topics inside the broad area of Soft Computing. Itsapplications as well as practical realizations can be found in all the real worldareas. In this paper a basic introduction to the main models and methods infuzzy mathematical programming, with special emphasis on those developedby the authors, is presented. As ...

in this paper, we study the finitely many constraints of fuzzy relation inequalities problem and optimize the linear objective function on this region which is defined with fuzzy max-lukasiewicz operator. in fact lukasiewicz t-norm is one of the four basic t-norms. a new simplification technique is given to accelerate the resolution of the problem by removing the components having no effect on ...

In three case studies on notions of fuzzy logic and fuzzy set theory (Dubois–Prade’s gradual elements, the entropy of a fuzzy set, and aggregation operators), the paper exemplifies methodological differences between traditional and deductive fuzzy logic. While traditional fuzzy logic admits various interpretations of membership degrees, deductive fuzzy logic always interprets them as degrees of...

In this paper, the finitely many constraints of a fuzzy relationinequalities problem are studied and the linear objective function on the regiondefined by a fuzzy max-average operator is optimized. A new simplificationtechnique which accelerates the resolution of the problem by removing thecomponents having no effect on the solution process is given together with analgorithm and a numerical exa...

In crisp transportation, trying to fuzzify the amount of supply of the ith origin ai and the amount of demand of the jth destination bj, we use level l fuzzy numbers and level (l, r) interval-valued fuzzy numbers to fuzzify ai and bj in the constraints. We get transportation problem in the fuzzy sense. We also cooperate some statistical concepts and corresponding to (1 α) × 100% statistical con...

One of the most important aspects of fuzzy systems is that they are easily understandable and interpretable. This property, however, does not come for free but poses some essential constraints on the parameters of a fuzzy system (like the linguistic terms), which are sometimes overlooked when learning fuzzy system automatically from data. In this paper, an objective function-based approach to l...

An attempt to solve fuzzy constraint satisfaction problems (FCSPs) with the use of genetic algorithms (GAS) is presented in the paper. A fuzzy relation that represents the degrees of Satisfaction of fuzzy constraints in a given FCSP is considered as an objective jimction of the respective unconstrained optimization problem. A solution of a FCSP such that all constraints are satisfied to the max...

This paper proposes an adaptive constraint based framework for fault detection of a complex thermal power plant system. In many complex systems, representation of precise and crisp constraints uses formal specification languages such as Object Constraint Language (OCL). Here, a constraint based neuro-fuzzy controller to tackle imprecise constrained objects is proposed. The proposed inference sy...