A new Probe Guided Mutation operator and its application for solving the cardinality constrained portfolio optimization problem

作者：

Highlights：

• A Probe Guided Mutation (PGM) proposed for efficient exploration of the search space.

• We use the PGM for solving the cardinality constrained portfolio optimization problem.

• The PGM is assessed through a number of indicators: Hypervolume, Spread and Epsilon.

• The PGM generates better results with confidence for all test problems examined.

摘要

•A Probe Guided Mutation (PGM) proposed for efficient exploration of the search space.•We use the PGM for solving the cardinality constrained portfolio optimization problem.•The PGM is assessed through a number of indicators: Hypervolume, Spread and Epsilon.•The PGM generates better results with confidence for all test problems examined.

论文关键词：Multiobjective optimization,Evolutionary algorithms,Mutation,Portfolio optimization,Cardinality constrained

论文评审过程：Available online 13 April 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.03.051