AbstractThis paper presents a suggested approach for solving a stochastic fuzzy linear programming problem. This approach utilizes two possibility and two necessity dominance indices that have been introduced by Dubois and Prade [D. Dubois, H. Prade, Ranking fuzzy numbers in the setting of possibility theory, Information Sciences 30 (1983) 183–224]. The chance-constrained approach and the α-cut are used to transform the stochastic fuzzy problem to its deterministic-crisp equivalent, according to each of the four dominance indices. A numerical example is given
Linear programming (LP) is the most widely used optimization technique for solving real-life problem...
This paper deals with the multi-objective chance constrained programming, where the right hand side ...
Abstract—In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stoch...
AbstractThis paper presents a suggested approach for solving a stochastic fuzzy linear programming p...
International audienceWe consider fuzzy stochastic programming problems with a crisp objective funct...
AbstractIn this paper, a suggested program with fuzzy linear fractional objectives and stochastic fu...
This paper considers linear programming problems (LPPs) where the objective functions involve discre...
AbstractIn this paper, a fuzzy multiobjective linear programming model is presented. Both the object...
The problems of linear programming are developing from time to time, and its complexity is constantl...
Interim Reports on work of the International Institute for Applied Systems Analysis receive only lim...
AbstractComparing fuzzy numbers, using the possibility programming approach, was presented by Negi a...
Based on the possibility measure and necessity measure, mλ-measure is presented and some mathematica...
This paper considers a linear programming problem with ellipsoidal distributions including fuzziness...
The present study focused on comparison of three defuzzification methods in transforming fuzzy two-s...
We introduce stochastic integer programs with dominance constraints induced by mixed-integer linear ...
Linear programming (LP) is the most widely used optimization technique for solving real-life problem...
This paper deals with the multi-objective chance constrained programming, where the right hand side ...
Abstract—In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stoch...
AbstractThis paper presents a suggested approach for solving a stochastic fuzzy linear programming p...
International audienceWe consider fuzzy stochastic programming problems with a crisp objective funct...
AbstractIn this paper, a suggested program with fuzzy linear fractional objectives and stochastic fu...
This paper considers linear programming problems (LPPs) where the objective functions involve discre...
AbstractIn this paper, a fuzzy multiobjective linear programming model is presented. Both the object...
The problems of linear programming are developing from time to time, and its complexity is constantl...
Interim Reports on work of the International Institute for Applied Systems Analysis receive only lim...
AbstractComparing fuzzy numbers, using the possibility programming approach, was presented by Negi a...
Based on the possibility measure and necessity measure, mλ-measure is presented and some mathematica...
This paper considers a linear programming problem with ellipsoidal distributions including fuzziness...
The present study focused on comparison of three defuzzification methods in transforming fuzzy two-s...
We introduce stochastic integer programs with dominance constraints induced by mixed-integer linear ...
Linear programming (LP) is the most widely used optimization technique for solving real-life problem...
This paper deals with the multi-objective chance constrained programming, where the right hand side ...
Abstract—In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stoch...