Abstract
This paper considers several portfolio selection problems including probabilistic future returns with ambiguous expected returns assumed as random fuzzy variables. Random fuzzy portfolio selection problems are formulated as nonlinear programming problems based on both stochastic and fuzzy programming approaches Since there is no efficient solution method to solve these problems directly, main problems are transformed into equivalent deterministic quadratic programming problems using probabilistic chance constraints, possibility measure and fuzzy goals, and their efficient solution methods to find a global optimal solution of each problem is constructed. Furthermore, numerical examples of portfolio selection problems are provided to illustrate our proposed models and solution methods compared with several previous basic models and to show that our proposed model is a versatile model to be applicable to various unexpected conditions.
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