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混合PSO的快速细菌觅食算法 被引量：8

Fast Bacterial Foraging Algorithm Combined with Particle Swarm Optimization
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摘要 为了提高细菌觅食算法在高维问题的收敛速度以及精度,提出了一种混合PSO的快速细菌觅食算法(FBFA-PSO).该算法用粒子的移动代替了细菌的趋化操作,省略了细菌前进操作,保留了细菌的繁殖和驱散操作.基于6个高维Benchmark函数的试验结果显示,该算法收敛速度和精度都优于其它三种细菌觅食算法. To improve the convergence speed and accuracy of the basic Bacterial Foraging Algorithm（BFA） over high dimensional problems,a fast bacterial foraging algorithm combined with Particle Swarm Optimization（FBFA-PSO） is presented.This algorithm uses the fly of particles instead of bacteria chemotaxis,and omits the swim of the bacteria,while it retains reproduction and elimination-dispersal of the bacteria.Simulation results on six benchmark functions show that the proposed algorithm is superior to other three bacterial foraging algorithms.
作者 麦雄发 李玲
机构地区 广西师范学院数学科学学院 广西师范学院继续教育学院
出处 《广西师范学院学报（自然科学版）》 2010年第4期91-94,118,共5页 Journal of Guangxi Teachers Education University(Natural Science Edition)
基金 广西教育厅科研项目(200911LX268) 广西师范学院基础研究基金项目(0810A004)
关键词 细菌觅食算法 粒子群优化 混合 Bacterial Foraging Algorithm Particle Swarm Optimization combine
分类号 TP18 [自动化与计算机技术—控制理论与控制工程]
  • 相关文献

参考文献7

  • 1K M PASSINO.Biomimicry of bacterial foraging for distributed optimization and control[J].IEEE Control Systems Magazine,2002,22(3):52-67.
  • 2KIM D H,ABRAHAM A,CHO J H.A hybrid genetic algorithm and bacterial foraging approach for global optimization[J].Information Sciences,2007,177(18):3918-3937.
  • 3BISWAS A,DASGUPTA S.Das S.Synergy of Differential Evolution and Bacterial Foraging Algorithm for Global Optimization[J].Neural Network World,2007,17(6):607-626.
  • 4A Biswas,S Dasgupta,S Das,and A.Abraham,Synergy of PSO and bacterial foraging optimization:A comparative study on numerical benchmarks[C].in Proc.2nd Int Symp.Hybrid Artificial Intell.Syst.(HAIS) Advances Soft Computing Ser.,Germany,Springer-Verlag,Innovations in Hybrid Intelligent Systems,ASC,2007,44:255-263.
  • 5Wael Mansour Korani.Bacterial foraging oriented by particle swarm optimization strategy for PID tuning[C].Proceedings of the 2008 GECCO conference companion on Genetic ane evolutionary computation,Atlanta,GA,USA,2008:12-16.
  • 6王雪松,程玉虎,郝名林.基于细菌觅食行为的分布估计算法在预测控制中的应用[J].电子学报,2010,38(2):333-339. 被引量：34
  • 7J Kennedy,R C Eberhart.Partide Swarm Optimization[C].in Proc.of the IEEE Int.Conf.on Neural Networks.Piscataway,NJ:IEEE Service Center,1995:1942-1948.

二级参考文献12

  • 1朱红霞,沈炯,丁轲轲.单元机组负荷非线性预测控制及其仿真研究[J].中国电机工程学报,2006,26(23):72-77. 被引量：12
  • 2Wang Xuesong, Cheng Yuhu, Sun Wei. Multi-step predictive control with TDBP method for pneumatic position servo system [ J]. Transactions of the Institute of Measurement and Control, 2006,28(1) :53 - 68.
  • 3Yuzgec U, Y. Becerikli, M. Turker. Nonlinear predictive control of a drying process using genetic algorithms[ J]. ISA Transactions,2006,45(4) :589 - 602.
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  • 6Passino K M. Biomimicry of bacterial foraging for distributed oplimizafion and control[ J]. IEEE, Control Systems Magazine, 2002,22(3) :52 - 67.
  • 7Tsutsui S,Pelikan M, Goldberg D E. Probabilistic model-building genetic algorithms using marginal histograms in continuous domain[ A ]. Proceedings of the International Conference on Knowledge Based Intelligent Information Engineering Systems and Allied Technology [ C ]. Amsterdam, Netherlands: IOS Press,2001.112 - 121.
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  • 10Matihew S, Terence S. Breeding swarms: a GA/PSO hybrid [ A ]. Proceedings of Genetic and Evolutionary Computation [ C]. New York: ACM Press. 2005. 161 - 168.

共引文献33

同被引文献56

  • 1李威武,王慧,邹志君,钱积新.基于细菌群体趋药性的函数优化方法[J].电路与系统学报,2005,10(1):58-63. 被引量：93
  • 2刘静,须文波,孙俊.基于量子粒子群算法求解整数规划[J].计算机应用研究,2007,24(3):79-81. 被引量：17
  • 3玄光男 程润伟.遗传算法与工程优化[M].北京:清华大学出版社,2004..
  • 4PASSINO K M. Biomimicry of bacterial foraging for distributed optimization and control[J]. IEEE Control Systems Magazine,2002, 22(3) :52-67.
  • 5KENNEDY J, EBERHART R C. Particle swarm optimization [ C ]// Proc of 1EEE International Conference on Neural Networks. Piscataway, NJ: IEEE Service Center, 1995 : 1942-1948.
  • 6BISWAS A, DASUPTA S, DAS S, et al. Synergy of PSO and bacterial foraging optimization: a comparative study on numerical benchmarks [ C ]//Proc of the 2nd International Symposium on Hybrid Artificial Intelligent Systems. Berlin : Springer-Verlag , 2007 : 255- 263.
  • 7KORANI W M. Bacterial foraging oriented by particle swarm optimization strategy for PID tuning[ C ]//Proc of GECCO Conference Companion on Genetic and Evolutionary Computation. New York: ACM Press ,2008 : 1823-1826.
  • 8刘小龙,李荣钧.基于粒子群算法的细菌觅食全局优化算法[EB/OL]. (2010-04-28). http://www. paperedu. cn/paper_oo0b51.
  • 9KAVEH A, SHOJAEE S. Optimal design of scissorlink foldable structures using ant colony optimization algorithm [J]. Computer-Aided Civil and Infrastructure Engineering, 2007, 22 (1): 72-80.
  • 10DORIGO M, DI CARO G, GAMBARDELLA L. Ant algorithms for discrete optimization [J]. Artificial Life, 1999, 5(3) :137-172.

引证文献8

二级引证文献15

广西师范学院学报（自然科学版）
2010年 第4期

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