A computational comparison between two evaluation criteria in fuzzy multiobjective linear programs using possibility programming

In 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.