Backtracking search algorithm with specular reflection learning for global optimization

作者：

Highlights：

• The specular reflection learning model is built.

• A new variant of BSA, called BSA_SRL, is proposed for global optimization.

• BSA_SRL is used for solving CEC 2013, CEC 2014 and CEC 2017 test suites.

• BSA_SRL is evaluated by constrained engineering optimization problems.

摘要

•The specular reflection learning model is built.•A new variant of BSA, called BSA_SRL, is proposed for global optimization.•BSA_SRL is used for solving CEC 2013, CEC 2014 and CEC 2017 test suites.•BSA_SRL is evaluated by constrained engineering optimization problems.

论文关键词：Opposition-based learning,Specular reflection learning,Backtracking search algorithm,Global optimization

论文评审过程：Received 18 June 2020, Revised 8 October 2020, Accepted 18 October 2020, Available online 1 November 2020, Version of Record 24 December 2020.

论文官网地址：https://doi.org/10.1016/j.knosys.2020.106546