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A dynamic multistage hybrid swarm intelligence optimization algorithm for function optimization

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成果类型:
期刊论文
作者:
Wu, Daqing*;Zheng, Jianguo
通讯作者:
Wu, Daqing
作者机构:
[Zheng, Jianguo; Wu, Daqing] DongHua Univ, Glorious Sun Sch Business & Management, Shanghai 200051, Peoples R China.
[Wu, Daqing] Univ S China, Comp Sci & Technol Inst, Hengyang 421001, Hunan, Peoples R China.
[Wu, Daqing] Sichuan Univ Sci & Engn, Artificial Intelligence Key Lab Sichuan Prov, Zigong 643000, Peoples R China.
通讯机构:
[Wu, Daqing] D
DongHua Univ, Glorious Sun Sch Business & Management, Shanghai 200051, Peoples R China.
语种:
英文
期刊:
Discrete Dynamics in Nature and Society
ISSN:
1026-0226
年:
2012
卷:
2012
期:
Pt.4
页码:
578064-1-578064-22
基金类别:
National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [70971020]; Open Project Program of Artificial Intelligence Key Laboratory of Sichuan Province (Sichuan University of Science and Engineering), China [2012RYJ03]; fund Project of Hunan province, China [11C1096]
机构署名:
本校为其他机构
院系归属:
计算机科学与技术学院
摘要:
A novel dynamic multistage hybrid swarm intelligence optimization algorithm is introduced, which is abbreviated as DM-PSO-ABC. The DM-PSO-ABC combined the exploration capabilities of the dynamic multiswarm particle swarm optimizer (PSO) and the stochastic exploitation of the cooperative artificial bee colony algorithm (CABC) for solving the function optimization. In the proposed hybrid algorithm, the whole process is divided into three stages. In the first stage, a dynamic multiswarm PSO is constructed to maintain the population diversity. In the second stage, the parallel, positive feedback o...

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