Evolutionary and adaptive inheritance enhanced Grey Wolf Optimization algorithm for binary domains

作者：

Highlights：

• A new binary gray wolf optimization algorithm is developed.

• Fitness-based and rank-based dominance strategies are developed.

• Multi-parent crossover and adaptive mutation are utilized.

• Set-Union Knapsack Problem and Uncapacitated Facility Location Problem are solved.

• Effectiveness of the algorithm is statistically verified.

摘要

•A new binary gray wolf optimization algorithm is developed.•Fitness-based and rank-based dominance strategies are developed.•Multi-parent crossover and adaptive mutation are utilized.•Set-Union Knapsack Problem and Uncapacitated Facility Location Problem are solved.•Effectiveness of the algorithm is statistically verified.

论文关键词：Binary optimization,Grey wolf optimization,Knapsack problem,Facility location problem,Multi-parent crossover

论文评审过程：Received 21 August 2019, Revised 26 January 2020, Accepted 28 January 2020, Available online 31 January 2020, Version of Record 18 May 2020.

论文官网地址：https://doi.org/10.1016/j.knosys.2020.105586