A multi-objective evolutionary algorithm for a class of mean-variance portfolio selection problems
作者：
Highlights：
• We solve several variants of the portfolio selection problem with a unified approach.
• A novel adaptive ranking procedure based on three mechanisms is introduced.
• Extensive computational experiments show the efficiency and robustness of the method.
摘要
•We solve several variants of the portfolio selection problem with a unified approach.•A novel adaptive ranking procedure based on three mechanisms is introduced.•Extensive computational experiments show the efficiency and robustness of the method.
论文关键词：Portfolio selection problem,Mean-variance,Multi-objective optimization,Particle swarm optimization,Unified algorithm
论文评审过程：Received 27 February 2019, Revised 21 April 2019, Accepted 14 May 2019, Available online 15 May 2019, Version of Record 23 May 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.05.018
