The aim of this paper is to solve the portfolio problem when security returns are birandom variables. Two types of portfolio selection based on chance measure are provided according to birandom theory. Since the proposed optimization problems are difficult to solve by traditional methods, a hybrid intelligent algorithm by integrating birandom simulation and genetic algorithm is designed. Finally, two numerical experiments are provided to illustrate the effectiveness of the algorithm.
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