TY - GEN
T1 - A Spherical Search-based Archive Update Mechanism for Self-adaptive Differential Evolution
AU - Zhang, Yu
AU - Lei, Zhenyu
AU - Zhang, Zhiming
AU - Todo, Yuki
AU - Tang, Zheng
AU - Gao, Shangce
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/3
Y1 - 2020/3
N2 - 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.
AB - 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.
KW - Computational intelligence
KW - differential evolution
KW - optimization
KW - spherical evolution
UR - http://www.scopus.com/inward/record.url?scp=85095599102&partnerID=8YFLogxK
U2 - 10.1109/ICAIIS49377.2020.9194937
DO - 10.1109/ICAIIS49377.2020.9194937
M3 - 会議への寄与
AN - SCOPUS:85095599102
T3 - Proceedings of 2020 IEEE International Conference on Artificial Intelligence and Information Systems, ICAIIS 2020
SP - 173
EP - 178
BT - Proceedings of 2020 IEEE International Conference on Artificial Intelligence and Information Systems, ICAIIS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Artificial Intelligence and Information Systems, ICAIIS 2020
Y2 - 20 March 2020 through 22 March 2020
ER -