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细菌菌落优化算法
引用本文:李明,杨成梧.细菌菌落优化算法[J].控制理论与应用,2011,28(2):223-228.
作者姓名:李明  杨成梧
作者单位:1. 西南林业大学,交通机械与土木工程学院,云南,昆明,650224
2. 南京理工大学,动力工程学院,江苏,南京,210094
基金项目:云南省应用基础研究面上资助项目(2009CD070); 云南省教育厅资助项目(08Y0204).
摘    要:根据细菌菌落生长演化的基本规律,提出一种新的细菌菌落优化算法.首先,依据细菌生长繁殖规律,制定符合算法需要的个体进化机制.其次根据细菌在培养液中的觅食行为,建立算法中个体泳动、翻滚、停留等运动方式.最后,借鉴菌落中细菌信息交互方式,建立个体信息共享机制.另外,该算法提供了一种新的结束方式,即在没有任何迭代次数或精度条件的前提下,算法会随着菌落的消失而自然结束,并且可以保持一定的精度.通过与两类PSO算法比较的仿真实验验证了细菌菌落优化算法的效果,通过仿真实验验证了细菌菌落优化算法自然结束过程.

关 键 词:菌落  群集智能  优化算法  进化机制
收稿时间:7/7/2009 12:00:00 AM
修稿时间:2009/12/13 0:00:00

Bacterial colony optimization algorithm
LI Ming and YANG Cheng-wu.Bacterial colony optimization algorithm[J].Control Theory & Applications,2011,28(2):223-228.
Authors:LI Ming and YANG Cheng-wu
Affiliation:College of Communication, Machinery and Civil Engineering, Southwest Forestry University,College of Power Engineering, Nanjing University of Science & Technology
Abstract:A bacterial colony optimization(BCO) algorithm based on the basic growth law of bacterial colony is presented. Firstly, an evolutionary mechanism for the individual of the BCO algorithm is designed by the reproduction law of bacterium. Secondly, swimming, tumbling and dwelling moving modes are established for the individual by the basic foraging theory of bacterium. Finally an information sharing method is built for the colony. This BCO algorithm provides a new type of termination: it will terminate the iteration when the colony vanishes, regardless of the iteration number or the precision value. The performance of the BCO algorithm is verified by some comparative simulations with two particle swarm optimization algorithms. Other simulations are employed to test the new termination type.
Keywords:bacterial colony  swarm intelligence  optimization algorithm  evolutionary mechanism
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