Interactive multiobjective random fuzzy programming problems through the possibility-based fractile model

This paper considers multiobjective linear programming problems where each coefficient of the objective functions is expressed by a random fuzzy variable. A new decision making model is proposed by incorporating the concept of fractile optimization into a possibilistic programming model in order to maximize both of possibility and probability with respect to the objective function values. An interactive algorithm is constructed to obtain a satisficing solution for a decision maker from among a set of Pareto optimal solutions.