Chun’an Liu1,*, Qian Lei2, Huamin Jia3
Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1477-1492, 2020, DOI:10.32604/iasc.2020.011853
Abstract Portfolio optimization is an effective way to diversify investment risk and optimize asset management. Many multiobjective optimization mathematical models and metaheuristic intelligent algorithms have been proposed to solve portfolio problem under an ideal condition. This paper presents a biobjective portfolio optimization model under the assumption of no short selling. In order to obtain sufficient number of portfolio optimal solutions uniformly distributed on the portfolio efficient Pareto front, a hybrid imperialist competitive evolutionary algorithm which combines a multi-colony levy crossover operator and a simple-colony moving operator with random perturbation is also given. The performance of the given algorithm is verified by… More >
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