一种具有量子行为的细菌觅食优化算法.pdfVIP

第35 卷第3 期 电 子 与 信 息 学 报 Vol.35 No.3 20 13 年3 月 Journal of Electronics Information Technology Mar. 2013 一种具有量子行为的细菌觅食优化算法 章国勇 伍永刚* 谭宇翔 (华中科技大学水电与数字化工程学院 武汉 430074) 摘 要：为改善细菌觅食优化(BFO)算法中群体信息共享机制，增强算法的全局有哪些信誉好的足球投注网站性能，该文将细菌个体放在量 子空间中描述，根据细菌群体信息建立量子化的势能阱模型，通过蒙特卡洛随机采样完成繁殖操作，使得细菌群能 对整个空间进行有哪些信誉好的足球投注网站。针对BFO 算法中趋化步长一致的缺陷，该文提出了一种动态缩进控制策略，在保证算法收 敛性的同时大大增加了个体全局寻优的几率。标准测试函数的仿真结果表明，所提出算法具有精度高、成功率大、 全局寻优性能强的特点。 关键词：信息处理；量子行为；细菌觅食；趋化步长；动态缩进 中图分类号：TP391 文献标识码： A 文章编号：1009-5896(2013)03-0614-08 DOI: 10.3724/SP.J.1146.2012.00892 Bacterial Foraging Optimization Algorithm with Quantum Behavior Zhang Guo-yong Wu Yong-gang Tan Yu-xiang (School of Hydropower and Informaiton Engineering, Huazhong University of Science and Teleology, Wuhan 430074, China) Abstract: In order to enhance the global optimization capability and quorum sensing mechanism of Bacterial Foraging Optimization (BFO) algorithm, a novel Bacterial Foraging Optimization algorithm with Quantum Behavior (QBFO) is proposed. In this method, the bacteria individual is described in the quantum space and a potential well model is created. Using Monte Carlo method to achieve the reproduction of bacterial swarming, and which makes the population are able to search the whole space. In view of the defects of the fixed swim step in bacterial foraging algorithm, a dynamic indented control strategy is introduced in this paper, which ensures the convergence of algorithm and increases the possibility of exploring a global optimum. The experiment results on classic functions demonstrate the global convergence ability of