Global optimization using novel randomly adapting particle swarm optimization approach

Nai Jen Li*, Wen June Wang, Chen Chien Hsu, Chih Min Lin

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

4 引文 斯高帕斯(Scopus)

摘要

This paper proposes a novel randomly adapting particle swarm optimization (RAPSO) approach which uses a weighed particle in a swarm to solve multi-dimensional optimization problems. In the proposed method, the strategy of the RAPSO acquires the benefit from a weighed particle to achieve optimal position in explorative and exploitative search. The weighed particle provides a better direction of search and avoids trapping in local solution during the optimization process. The simulation results show the effectiveness of the RAPSO, which outperforms the traditional PSO method, cooperative random learning particle swarm optimization (CRPSO), genetic algorithm (GA) and differential evolution (DE) on the 6 benchmark functions.

原文英語
主出版物標題2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011 - Conference Digest
頁面1783-1787
頁數5
DOIs
出版狀態已發佈 - 2011
事件2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011 - Anchorage, AK, 美国
持續時間: 2011 十月 92011 十月 12

出版系列

名字Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN(列印)1062-922X

其他

其他2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011
國家/地區美国
城市Anchorage, AK
期間2011/10/092011/10/12

ASJC Scopus subject areas

  • 電氣與電子工程
  • 控制與系統工程
  • 人機介面

指紋

深入研究「Global optimization using novel randomly adapting particle swarm optimization approach」主題。共同形成了獨特的指紋。

引用此