Hybrid ICA–PSO algorithm for continuous optimization

作者：

Highlights：

• A novel hybrid metaheuristic fro continuous problems is proposed.

• The algorithm combines particle swarm optimization (PSO) and imperialist competitive algorithms (ICA).

• Algorithm performance is tested on several single and multi-objective problems.

• Results show that the algorithm outperforms NSGA-II and SPEA2.

摘要

•A novel hybrid metaheuristic fro continuous problems is proposed.•The algorithm combines particle swarm optimization (PSO) and imperialist competitive algorithms (ICA).•Algorithm performance is tested on several single and multi-objective problems.•Results show that the algorithm outperforms NSGA-II and SPEA2.

论文关键词：Imperialist competitive algorithm,Particle swarm optimization,Hybrid algorithm,Mono-objective and multi-objective benchmark functions

论文评审过程：Available online 21 June 2013.

论文官网地址：https://doi.org/10.1016/j.amc.2013.05.027