This paper considers linear programming problems where each coefficient of the objective function is expressed by a random fuzzy variable. New decision making models are proposed based on stochastic and possibilistic programming in order to maximize both of possibility and probability with respect to the objective function value. It is shown that each of the proposed models is transformed into a deterministic equivalent one. Solution algorithms using convex programming techniques and/or the bisection method are provided for obtaining an optimal solution of each model.
|Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
|Published - 2008
|2008 IEEE International Conference on Systems, Man and Cybernetics, SMC 2008 - Singapore, Singapore
継続期間: 2008 10月 12 → 2008 10月 15
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