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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)
date.issued: 2009
citation.conferencedate: June 12–14, 2009
description.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.
citation.conferencename: ACM/SIGEVO Summit on Genetic and Evolutionary Computation  
citation.source: Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
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]. Proceedings Of The First Acm/sigevo Summit On Genetic And Evolutionary Computation.New York.Acm.2009,497-504.

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