AbstractIn this paper, a fuzzy multiobjective linear programming model is presented. Both the objective functions and the constraints are considered fuzzy. The coefficients of the decision variables in the objective functions and in the constraints, as well as the right-hand side of the constraints are assumed to be fuzzy numbers with either trapezoidal or triangular membership functions. The possibility programming approach is utilized to transform the fuzzy model to its crisp equivalent. A comparison between the global criterion method and the distance functions method, as two evaluation criteria, is illustrated by a computational study
This paper proposes a new method to evaluate Decision Making Units (DMUs) under uncertainty using fu...
We investigate various types of fuzzy linear programming problems based on models and solution metho...
AbstractThis paper presents a suggested approach for solving a stochastic fuzzy linear programming p...
AbstractComparing fuzzy numbers, using the possibility programming approach, was presented by Negi a...
AbstractIn this paper, a suggested program with fuzzy linear fractional objectives and stochastic fu...
In modelling and optimizing real world systems and processes, one usually ends up with a linear or n...
Linear programming (LP) is the most widely used optimization technique for solving real-life problem...
Abstract This paper formulates multiobjective linear programming problems where each coefficient of ...
Abstract—In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stoch...
Two approaches to the analysis of multiobjective programming problems are presented based on a syste...
Fuzzy linear programming problems have an essential role in fuzzy modeling, which can formulate unce...
This study considers multiobjective fuzzy linear programming (MFLP) problems in which the coefficien...
Many business decisions can be modeled as multiple objective linear programming (MOLP) problems. Whe...
Abstract:- In the real-world optimization problems, coefficients of the objective function are not k...
Abstract – The two well known methods for solving the linear programming problems are, i) Convertin...
This paper proposes a new method to evaluate Decision Making Units (DMUs) under uncertainty using fu...
We investigate various types of fuzzy linear programming problems based on models and solution metho...
AbstractThis paper presents a suggested approach for solving a stochastic fuzzy linear programming p...
AbstractComparing fuzzy numbers, using the possibility programming approach, was presented by Negi a...
AbstractIn this paper, a suggested program with fuzzy linear fractional objectives and stochastic fu...
In modelling and optimizing real world systems and processes, one usually ends up with a linear or n...
Linear programming (LP) is the most widely used optimization technique for solving real-life problem...
Abstract This paper formulates multiobjective linear programming problems where each coefficient of ...
Abstract—In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stoch...
Two approaches to the analysis of multiobjective programming problems are presented based on a syste...
Fuzzy linear programming problems have an essential role in fuzzy modeling, which can formulate unce...
This study considers multiobjective fuzzy linear programming (MFLP) problems in which the coefficien...
Many business decisions can be modeled as multiple objective linear programming (MOLP) problems. Whe...
Abstract:- In the real-world optimization problems, coefficients of the objective function are not k...
Abstract – The two well known methods for solving the linear programming problems are, i) Convertin...
This paper proposes a new method to evaluate Decision Making Units (DMUs) under uncertainty using fu...
We investigate various types of fuzzy linear programming problems based on models and solution metho...
AbstractThis paper presents a suggested approach for solving a stochastic fuzzy linear programming p...