Interactive fuzzy programming for multiobjective fuzzy random linear programming problems through possibility-based probability maximization

This paper presents interactive fuzzy programming for multiobjective fuzzy random linear programming problems through possibility-based probability maximization. In our proposed approach, it is assumed that the decision maker has fuzzy goals for not only original objective functions but also the corresponding distribution functions in a probability maximization model, and such fuzzy goals are quantified by eliciting the corresponding membership functions. Using the fuzzy decision, such two kinds of membership functions are integrated. The satisfactory solution is derived from among an extended Pareto optimal solution set through the interaction with the decision maker. An illustrative numerical example is provided to demonstrate the efficiency of the proposed method.