A new class of fuzzy stochastic optimization models—two-stage fuzzy stochastic programming with Value-at-Risk (FSP-VaR) criteria is built in this paper. Some properties of the two-stage FSP-VaR, such as value of perfect information (VPI), value of fuzzy random solution (VFRS), and bounds of the fuzzy random solution, are discussed. An Approximation Algorithm is proposed to compute the VaR by co...

This paper presents portfolio selection problems with ambiguous returns assumed as “return is about ξ” which is neither estimated by randomness nor fuzziness. Portfolio selection problems in uncertain environment are formulated as nonlinear programming models based on uncertain programming approaches. Since there is no efficient solution method to solve these problems directly, original problem...

The concept of duality plays an important role in optimization theory .In this paper, a new method is proposed to find the fuzzy optimal solution of fully fuzzy linear programming problems using breaking point and duality theory. By using the proposed method the fuzzy optimal solution of fully fuzzy linear programming problem with inequality constraints has been obtained. To illustrate the prop...

Quadratic programming (QP) is an optimization problem wherein one minimizes (or maximizes) a quadratic function of a finite number of decision variable subject to a finite number of linear inequality and/ or equality constraints. In this paper, a quadratic programming problem (FFQP) is considered in which all cost coefficients, constraints coefficients, and right hand side are characterized by ...

abstract regarding the imprecise or fuzzy data on the agriculture activities, applying models based on fuzzy data may be useful. in line with this condition this study tries to compare the ability of possiblistic programming approach in developing optimal solution with fuzzy and deterministic programming. to get this objective a data set obtained from 90 farmers of kohgilooye region, gathered i...