A multi-objective optimization algorithm based on subgroup stratified coarse-grained model and its application

Timing Li, Yongzhe Zhang, Kewen Li, Yongqi Liang, Xiangbo Ma

Abstract: The subgroup stratified coarse-grained particle swarm optimization model is proposed, in which the subgroups play different roles in the evolution process to improve the performance of PSO algorithms.•The proposed algorithm can dynamically adjust the evolution strategy by the update situation of the Pareto solution set and increase perturbation of the local extremum to improve stability and optimization performance.•The proposed algorithm is applied to solve the constrained multi-objective web service composition optimization problem and has achieved better comprehensive performance.