An Improved Cooperative RDPSO Algorithm Based on Search History Decision

A novel cooperative RDPSO algorithm based on entire search history decision (CRDPSO) is reported. The proposed algorithm employs a binary space partitioning tree structure to memorize the positions and the fitness values of the evaluated solution. Benefiting from the space partitioning scheme, a fast fitness function approximation using the archive is obtained. The approximation is used to improve the mutation strategy in CRDPSO. The resultant mutation is adaptive and parameter-less. Meanwhile, the cooperation mechanism enhanced search ability helps to prevent premature convergence and improve optimization. The proposed algorithm is examined on 8 standard benchmark functions including multimodal and unimodal functions. The results show that CRDPSO outperforms four traditional algorithms.