A Spherical Search-based Archive Update Mechanism for Self-adaptive Differential Evolution

Recently, meta-heuristic algorithms have been researched in quantity. However, there are no algorithms applying to different problems effectively and having notable difference compared with other meta-heuristic algorithm. Evolutionary algorithms are classical algorithms of nature-inspired metaheuristic algorithms. Spherical evolution (SE) is one of metaheuristic algorithms proposed recently. SE uses a spherical search style rather than the traditional hypercube search style. Differential evolution (DE) is a classical algorithm of hypercube search style. In this paper, considering the strong exploration capability of SE and the powerful exploitation ability of DE, we synthesize two search style and propose a hybrid algorithm, and use archive to reuse the good individuals. The proposed algorithm exhibits better performance in comparison with other state-of-the-art algorithms in terms of robustness and effectiveness based on 30 benchmark functions of IEEE CEC2017.