Particle swarm optimization incorporating simplex search and center particle for global optimization

Chen Chien Hsu, Chun Hwui Gao

研究成果: 書貢獻/報告類型會議貢獻

9 引文 斯高帕斯(Scopus)

摘要

This paper proposes a hybrid approach incorporating an enhanced Nelder-Mead simplex search scheme into a particle swarm optimization (PSO) with the use of a center particle in a swarm for effectively solving multi-dimensional optimization problems. Because of the strength of PSO in performing exploration search and NM simplex search in exploitation search, in addition to the help ofa center particle residing closest to the optimum during the optimization process, both convergence rate and accuracy of the proposed optimization algorithm can be significantly improved. To show the effectiveness of the proposed approach, 18 benchmark functions will be adopted for optimization viathe proposed approach in comparison to existing methods.

原文英語
主出版物標題SMCia/08 - Proceedings of the 2008 IEEE Conference on Soft Computing on Industrial Applications
頁面26-31
頁數6
DOIs
出版狀態已發佈 - 2008 十二月 1
事件2008 IEEE Conference on Soft Computing on Industrial Applications, SMCia/08 - Muroran, 日本
持續時間: 2008 六月 252008 六月 27

出版系列

名字SMCia/08 - Proceedings of the 2008 IEEE Conference on Soft Computing on Industrial Applications

其他

其他2008 IEEE Conference on Soft Computing on Industrial Applications, SMCia/08
國家日本
城市Muroran
期間08/6/2508/6/27

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Software
  • Industrial and Manufacturing Engineering

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  • 引用此

    Hsu, C. C., & Gao, C. H. (2008). Particle swarm optimization incorporating simplex search and center particle for global optimization. 於 SMCia/08 - Proceedings of the 2008 IEEE Conference on Soft Computing on Industrial Applications (頁 26-31). [5045930] (SMCia/08 - Proceedings of the 2008 IEEE Conference on Soft Computing on Industrial Applications). https://doi.org/10.1109/SMCIA.2008.5045930