[1]姜建国,周佳薇,郑迎春,等.一种双菌群细菌觅食优化算法[J].深圳大学学报理工版,2014,31(No.1(001-110)):43-51.[doi:10.3724/SP.J.1249.2014.01043]
 Jiang Jianguo,Zhou Jiawei,Zheng Yingchun,et al.A double flora bacteria foraging optimization algorithm[J].Journal of Shenzhen University Science and Engineering,2014,31(No.1(001-110)):43-51.[doi:10.3724/SP.J.1249.2014.01043]
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一种双菌群细菌觅食优化算法()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第31卷
期数:
2014年No.1(001-110)
页码:
43-51
栏目:
电子与信息科学
出版日期:
2014-01-14

文章信息/Info

Title:
A double flora bacteria foraging optimization algorithm
文章编号:
20140106
作者:
姜建国1周佳薇1郑迎春12周润生3
1)西安电子科技大学计算机学院,西安 710071
2)中国电子科技集团公司第五十四研究所,石家庄 050081
3)渭南职业技术学院,陕西渭南 714000
Author(s):
Jiang Jianguo1 Zhou Jiawei1 Zheng Yingchun12 and Zhou Runsheng3
1)School of Computer Science and Technology, Xidian University, Xi’an 710071, P.R.China
2)The Fifty-fourth Research Institute of China Electronic Technology Group Corporation, Shijiazhuang 050081, P.R.China
3)Weinan Vocational & Technical College, Weinan 714000, Shaanxi Province, P.R.China
关键词:
人工智能细菌觅食优化算法双菌群局部最优自适应步长交叉算子变异算子
Keywords:
artificial intelligence bacterial foraging optimization algorithm double flora local optimization adaptive step crossover mutation
分类号:
TP 301.6
DOI:
10.3724/SP.J.1249.2014.01043
文献标志码:
A
摘要:
针对细菌觅食优化算法寻优速度慢且易陷入局部最优等缺陷,提出一种双菌群细菌觅食优化算法.引入菌群密度函数因子,并添加当前趋化周期内的最优细菌对其他细菌在寻优方向上进行指导,同时改进固定步长为自适应变化的趋化步长,避免了在最优解附近出现震荡现象及算法陷入局部最优;保留精英细菌的同时提出交叉算子和变异算子,有目的地在搜索区域寻找最优解,帮助早熟细菌跳出局部最优,一定程度上避免了算法早熟;提出双菌群优化机制,增加了菌群的多样性,提高了算法的全局搜索能力,有效抑制算法退化现象.对10个经典测试函数的仿真结果表明,所提出的算法与细菌觅食优化(bacterial foraging optimization,BFO)算法相比,最优解的精度普遍提高了几个数量级,且迭代次数更少,优化速度与全局收敛能力均有所提升.
Abstract:
A double flora bacterial foraging optimization algorithm is presented to solve the problems of slow convergence and local optimization. The bacteria density factor is introduced, and the optimization direction to another bacterium is guided by the current optimal bacteria. The adaptive chemotactic step is used instead of fixed step to avoid turbulence near the optimal solution and to obtain partial optimal solutions. The crossover and the mutation operators are proposed and the elite bacterium is retained to find the optimal solution in the search area efficiently. Therefore, the premature bacteria are helped to jump out of the local optimal solution to a certain extent. A double flora optimization mechanism is formulated to increase the diversity of flora, to enhance the global search capability and suppress the degeneracy phenomenon. The simulation results of ten benchmark functions have demonstrated that the solution accuracy of proposed algorithm is generally improved by several orders of magnitude in comparison with standard bacterial foraging optimization, and fewer iterations are needed. Both optimization speed and global convergence ability are improved.

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备注/Memo

备注/Memo:
Received:2013-08-11;Revised:2013-12-02;Accepted:2013-12-09
Foundation:National Defense Basic Research Program (A11***007)
Corresponding author:Professor Jiang Jianguo.E-mail:jgjiang@mail.xidian.edu.cn
Citation:Jiang Jianguo,Zhou Jiawei,Zheng Yingchun, et al.A double flora bacteria foraging optimization algorithm[J]. Journal of Shenzhen University Science and Engineering, 2014, 31(1): 43-51.(in Chinese)
基金项目:国防基础科研计划资助项目(A11***007)
作者简介:姜建国(1956-),男(汉族),陕西省西安市人,西安电子科技大学教授.E-mail:jgjiang@mail.xidian.edu.cn
引文:姜建国,周佳薇,郑迎春,等.一种双菌群细菌觅食优化算法[J]. 深圳大学学报理工版,2014,31(1):43-51.
更新日期/Last Update: 2014-01-08