A self-adaptive harmony PSO search algorithm and its performance analysis

作者：

Highlights：

• A self-adaptive harmony particle swarm optimization search algorithm is proposed.

• PSO algorithm is utilized to initial the harmony memory (HM).

• Pitch adjusting rate (PAR) and distance bandwidth (bw), are adjusted dynamically.

• A Gaussian mutation operator is added to reinforce the robustness.

• The convergence of the SHPSOS algorithm has been proved theoretically.

摘要

•A self-adaptive harmony particle swarm optimization search algorithm is proposed.•PSO algorithm is utilized to initial the harmony memory (HM).•Pitch adjusting rate (PAR) and distance bandwidth (bw), are adjusted dynamically.•A Gaussian mutation operator is added to reinforce the robustness.•The convergence of the SHPSOS algorithm has been proved theoretically.

论文关键词：Harmony Search algorithm,PSO algorithm,Self-adaptive scheme,Mutation strategy,Markov model

论文评审过程：Available online 27 May 2015, Version of Record 17 June 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.05.035