Abstract
In the paper, a particle surface-simplex search (PSSS) is designed based on particle surface-simplex and particle surface- simplex neighborhood. Using PSSS and an evolutionary strategy of multi-states swarm, a surface-simplex swarm evolution (SSSE) algorithm for numerical optimization is proposed. In the experiments, SSSE is applied to solve 17 benchmark problems and compared with the other intelligent optimization algorithms. In the application, SSSE is used to analyze the three intrinsic independent components of gravity earth tide. The results demonstrate that SSSE can accurately find optima or close-to-optimal solutions of the complex functions with high-dimension. The performance of SSSE is stable and efficient.
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Foundation item: Supported by the National Natural Science Foundation of China (41364002)
Biography: QUAN Haiyan, male, Ph.D., Associate professor, research direction: optimization algorithm, signal processing.
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Quan, H., Shi, X. A surface-simplex swarm evolution algorithm. Wuhan Univ. J. Nat. Sci. 22, 38–50 (2017). https://doi.org/10.1007/s11859-017-1214-9
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DOI: https://doi.org/10.1007/s11859-017-1214-9
Keywords
- evolutionary computation
- global optimization
- particle surface-simplex
- surface-simplex swarm evolution
- multistates swarm
- gravity earth tide