Interactive multiobjective random fuzzy programming: Necessity-based value at risk model

This article considers multiobjective linear programming problems (MOLPP) where random fuzzy variables are contained in objective functions and constraints. The purpose of the proposed decision making model is to optimize values at risk under the constraints using a necessity measure. An interacitve algorithm is constructed in order to obtain a satisficing solution for the decision maker from among a set of Pareto optimal solutions.

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