模糊投资组合选择问题的改进帝企鹅优化算法

Improved Emperor Penguin Optimizer for Fuzzy Portfolio Selection

模糊投资组合选择问题是在基本投资组合模型中引入模糊集理论,使所建立的模型与实际市场更加吻合,但同时也增加了模型求解难度.因此,本文针对两种不同的模糊投资组合模型,提出一种改进帝企鹅优化算法.算法首先引入可行性准则,处理模糊投资组合模型中的约束.其次,算法中加入变异机制,平衡算法的开发和探索能力,引导种群向最优个体收敛.通过对CEC 2006中的13个标准测试问题及两个模糊投资组合问题实例进行数值实验,并与其他群智能优化算法进行结果比较,发现本文所提出的算法具有较好的优化性能,并且对于求解模糊投资组合选择问题是有效的.

The introduction of fuzzy theory into basic portfolio selection model can make the model more consistent with the actual market,but also increasing the dificulty for solving the model.Therefore,an improved emperor penguin optimizer for two different fuzzy portfolio models is proposed in this paper.The algorithm first introduces feasibility criteria to deal with constraints in fuzzy portfolio models.Secondly,the mutation mechanism is added in the algorithm to balance the exploitation ability and exploration ability,which can guide the population to converge towards the optimal individual.Through the numerical experiments on 13 standard test problems of CEC 2006 and two fuzzy portfolio selection problems,the results are compared with those of other swarm intelligence optimization algorithms.It is found that the algorithm proposed in this paper has good optimization performance,and it is effective to solve the fuzzy portfolio selection problem.