Nonlinear fuzzy chance constrained approach for multi-objective mixed fuzzy-stochastic optimization problem

Fuzzy set theory currently has a wide range of applications to model real-world issues with ambiguous or incomplete information, which to some extent captures reality. On the other hand stochastic environment also deals with uncertainties with different approach (probability distribution). In order to deal with decision problems involving more than one objective, where the parameters and the objectives both are uncertain, the mixed fuzzy stochastic programming approach have been introduced. In this paper, a new solution named as fuzzy stochastic pareto optimal solution is defined. Here we have developed an iterative method for the decision making of a multi-objective optimization problem in the fuzzy stochastic environment. Further a numerical illustration of the developed methodology has been given and the superiority of the proposed method has been established by comparing the obtained results with some well known existing methods.