[PDF] Top 20 An Algorithm for Solving Fuzzy Relation Programming with the Max-T Composition Operator

... Fuzzy Relation Equations (FRE) and the problems related to them have been stud- ied by many researchers since the resolution of fuzzy relation equations was proposed by Sanchez [12] in 1976 ... See full document

... new algorithm is proposed to solve the fuzzy relation equation P ◦ Q = R with max–min composition and max–product composition in ... See full document

... Dombi t-norm) were proposed to sim- plify the ...the max- Dombi fuzzy relational equations, and then a genetic algorithm was designed for solving the nonlinear optimization problems ... See full document

... of fuzzy relation inequalities problem and opti- mize the linear objective function on this region which is defined with fuzzy max-Lukasiewicz ...Lukasiewicz t-norm is one of the four ... See full document

... min-s-norm composition is “equally interesting and important, but less known” compared to commonly known ...min-s fuzzy relational equations by using a method similar to that for solving ... See full document

... of fuzzy relational equations or in- equalities (FRI) is one of the most interesting and on-going topics among the problems re- lated to the FRE (or FRI) theory ...the max-min composition ...linear ... See full document

... index algorithm for solving the minimization of linear objective function subject to FRI with addition-min ...to max-product fuzzy relation ...of fuzzy relational inequalities ... See full document

... geometric programming problem subject to MFRI with two operators of max- product and max-Hamacher composition is studied in this ...an algorithm was designed to solve the ... See full document

... different composition operators was given in 1980s, see for instance ...continuous max t-norm is determined by one maximum solution and finite number of minimal ... See full document

... index algorithm for solving the minimization of linear objective function subject to FRI with addition-min ...to max-product fuzzy relation inequalities with application in the ... See full document

... As we discussed, the optimal solution of sub-problem P2 is easily obtained. But it is necessary to search minimal solutions of feasible region, i.e., X[A, b], for finding optimal solution of sub-problem P1. Theorem 5 ... See full document

... goal programming needs the additional information from decision makers for priority structure of var- ious goals and their respective aspiration ...a fuzzy approach to multiobjective linear ... See full document

... fractional programming problem (MOLFPP) by using fuzzy set theoretic ...linear programming problem (MOLPP) by suitable transformation. In algorithm-I, MOLFPP is transformed into MOLPP by using ... See full document

... for solving a class of fuzzy linear programming (FLP) problems involving symmetric trapezoidal fuzzy numbers without converting them to crisp linear programming problems are the ... See full document

... fractional programming problems in which odd numbered fractional objective functions of the problem are converted into linear objective functions by subtracting the denominator function from the numerator function ... See full document

... Linear programming is concerned with the opti- mization (minimization or maximization) of a lin- ear function while satisfying a set of linear equal- ity and/ or inequality constrains or ...linear ... See full document

... intuitionistic fuzzy sets/numbers [6] [7] [8] [9] ...order fuzzy sets, intuitionistic fuzzy set introduced by Atanassov [11] [12] [13] [14] has been found to be highly useful in dealing with ...this ... See full document

... and fuzzy variables [1]; Renewal processes where inter-arri- val times are only known as subjective categories of the form; almost 3 hours, around 2 hours, less than 4 hours…, the occurrence of which cannot be ... See full document

... Generally, solution methods of multi-objective linear programming problems may be classified into three groups, viz:priori, interactive, and posterior methods [4]. In a priori method, the decision maker states his ... See full document

... The Dynamic Programming technique is used to solve optimal subdivision problems. For example, a positive quantity can be divided into some sub-quantities whose sum of cubes or squared sums or product may be ... See full document