A filter-based artificial fish swarm algorithm for constrained global optimization: theoretical and practical issues
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DOI: 10.1007/s10898-014-0157-3
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Cited by:
- M. Joseane F. G. Macêdo & Elizabeth W. Karas & M. Fernanda P. Costa & Ana Maria A. C. Rocha, 2020. "Filter-based stochastic algorithm for global optimization," Journal of Global Optimization, Springer, vol. 77(4), pages 777-805, August.
- C. J. Price & M. Reale & B. L. Robertson, 2016. "Stochastic filter methods for generally constrained global optimization," Journal of Global Optimization, Springer, vol. 65(3), pages 441-456, July.
- Ling Wang & Lu An & Jiaxing Pi & Minrui Fei & Panos M. Pardalos, 2017. "A diverse human learning optimization algorithm," Journal of Global Optimization, Springer, vol. 67(1), pages 283-323, January.
- Xiaobing Yu & Yiqun Lu & Mei Cai, 2018. "Evaluating agro-meteorological disaster of China based on differential evolution algorithm and VIKOR," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 94(2), pages 671-687, November.
- M. Fernanda P. Costa & Ana Maria A. C. Rocha & Edite M. G. P. Fernandes, 2018. "Filter-based DIRECT method for constrained global optimization," Journal of Global Optimization, Springer, vol. 71(3), pages 517-536, July.
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Keywords
Global optimization; Artificial fish swarm; Filter method; Stochastic convergence;All these keywords.
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