A two-stage differential biogeography-based optimization algorithm and its performance analysis

作者：

Highlights：

• A two-stage differential biogeography-based optimization (TDBBO) is proposed.

• A migration model based on the two-stage mechanism is proposed.

• A BBO/current − to − select/1 is designed to alleviate the rotational variant.

• Gaussian mutation is employed to enhance the exploration ability.

• The convergence performance of TDBBO is analyzed with the Markov model.

摘要

•A two-stage differential biogeography-based optimization (TDBBO) is proposed.•A migration model based on the two-stage mechanism is proposed.•A BBO/current − to − select/1 is designed to alleviate the rotational variant.•Gaussian mutation is employed to enhance the exploration ability.•The convergence performance of TDBBO is analyzed with the Markov model.

论文关键词：Biogeography-based optimization,Two-stage mechanism,Rotational variance,Gaussian mutation,Markov model

论文评审过程：Received 23 January 2018, Revised 9 August 2018, Accepted 10 August 2018, Available online 11 August 2018, Version of Record 20 August 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.08.012