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Title: Bacterial foraging optimization algorithm with particle swarm optimization strategy for global numerical optimization
Author: Shen H(申海) ;  Zhu YL(朱云龙) ;  Zhou XM(周小明) ;  Guo HF(郭海峰) ;  Chang CG(常春光)
Department: 先进制造技术实验室
Conference Name: ACM/SIGEVO Summit on Genetic and Evolutionary Computation  
Conference Date: June 12–14, 2009
Conference Place: Shanghai, China
Sponsorship: ACM
Source: Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Publisher: ACM
Publish Place: New York
Issued Date: 2009
Pages: 497-504
Indexed Type: CPCI(ISTP) ;  EI
ISBN: 978-1-60558-326-6
Keyword: bacterial foraging ;  numerical optimization ;  particle swarm optimization
Abstract: In 2002, K. M. Passino proposed Bacterial Foraging Optimization Algorithm (BFOA) for distributed optimization and control. One of the major driving forces of BFOA is the chemotactic movement of a virtual bacterium that models a trial solution of the optimization problem. However, during the process of chemotaxis, the BFOA depends on random search directions which may lead to delay in reaching the global solution. Recently, a new algorithm BFOA oriented by PSO termed BF-PSO has shown superior in proportional integral derivative controller tuning application. In order to examine the global search capability of BF-PSO, we evaluate the performance of BFOA and BF-PSO on 23 numerical benchmark functions. In BF-PSO, the search directions of tumble behavior for each bacterium oriented by the individual's best location and the global best location. The experimental results show that BF-PSO performs much better than BFOA for almost all test functions. That's approved that the BFOA oriented by PSO strategy improve its global optimization capability.
Language: 英语
Rank: 1
Content Type: 会议论文
URI: http://ir.sia.cn/handle/173321/8163
Appears in Collections:工业信息学研究室_先进制造技术研究室_会议论文

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Recommended Citation:
Shen H,Zhu YL,Zhou XM,et al. Bacterial foraging optimization algorithm with particle swarm optimization strategy for global numerical optimization[C]. 见:ACM/SIGEVO Summit on Genetic and Evolutionary Computation  . Shanghai, China. June 12–14, 2009.
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