| 引用本文: | 刘文霞,刘晓茹,张建华,刘 念.基于微分进化和混沌迁移的细菌群体趋药性算法[J].控制理论与应用,2009,26(4):353~357.[点击复制] |
| LIU Wen-xia,LIU Xiao-ru,ZHANG Jian-hua,LIU Nian.Bacterial colony chemotaxis algorithm based on differential evolution and chaos migration[J].Control Theory and Technology,2009,26(4):353~357.[点击复制] |
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| 基于微分进化和混沌迁移的细菌群体趋药性算法 |
| Bacterial colony chemotaxis algorithm based on differential evolution and chaos migration |
| 摘要点击 1452 全文点击 1307 投稿时间：2007-12-09 修订日期：2008-11-19 |
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| DOI编号 |
| 2009,26(4):353-357 |
| 中文关键词 细菌群体趋药性算法 参数控制 动态感知范围 微分策略 混沌迁移机制 |
| 英文关键词 bacterial colony chemotaxis algorithm parameters control dynamic sense limit differential strategy strategy of chaotic migration |
| 基金项目 华北电力大学 博士学位科研基金资助项目(200722004). |
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| 中文摘要 |
| 细菌群体趋药性(BCC)算法是一种新的群体智能优化算法. 本文研究了BCC算法中群体控制参数对算法性能的影响, 并提出算法应用的参数控制策略. 标准的BCC算法存在易于陷入局部极值的缺点, 因此新算法中采用了以下改进措施, 自适应调整感知范围、当细菌确定下一步位置时增加微分进化的待选个体和采用混沌迁移机制, 改进后的算法增强了跳出局部最优解的能力. 实验结果表明, 新算法的全局搜索能力有了显著提高. |
| 英文摘要 |
| Bacterial colony chemotaxis (BCC) algorithm is a new colony intelligence optimization algorithm. The influence of the relative parameters to the performance of BCC is studied; and the control strategies for parameters are proposed. The basic BCC algorithm has the disadvantage of being trapped into the local minimum. Therefore, some improvements are adopted in the new algorithm, including adjusting the perception scope of self-adaptation, adding differential evolutionary individual when the bacteria choose their next locations, and taking chaos transfer mechanism. The ability to get rid of the local optimum is thus greatly improved. Finally, the experimental results show that the new algorithm improves the global optimization performance. |
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