关键词: 可信性理论, 粒子群算法, Pareto最优曲面, 投资组合

Abstract: Considering that investors are often faced with both random and fuzzy uncertainty in the securities market, in this paper, we regard securities yield as a triangular fuzzy variable. We build a mean-entropy-skewness portfolio model on the basis of credibility theory to extend the research about portfolio model based on credibility theory. At the same time, an improved constrained multi-objective particle swarm optimization algorithm is proposed by improving the key operators such as constraint condition method and the pareto optimal solutions maintenance method. The feasible solution is compared with the feasible solution generated by traditional multi-objective particle swarm optimization algorithm. The results show that the solution of the improved constrained multi-objective particle swarm algorithm is superior to that generated by traditional multi-objective particle swarm optimization algorithm. The feasibility and accuracy of the algorithm is verified, and the pareto optimal surface with better distribution and approximation can be obtained in three-dimensional space to meet the demand of different target, to provide investors with a reasonable portfolio decision.

Key words: credibility theory, particle swarm algorithm, pareto optimal surface, investment portfolio