| 增强寻优能力的自适应人工蜂群算法* |
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| 引用本文： | 张泰,屠思远,吴滨,顾晓峰.增强寻优能力的自适应人工蜂群算法*[J].计算机应用研究,2016,33(10). |
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| 作者姓名： | 张泰 屠思远 吴滨 顾晓峰 |
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| 作者单位： | 轻工过程先进控制教育部重点实验室,轻工过程先进控制教育部重点实验室,轻工过程先进控制教育部重点实验室,轻工过程先进控制教育部重点实验室 |
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| 基金项目： | 江苏省科技厅产学研联合创新资金(BY2013015-19)；中央高校基本科研业务费专项资金(JUSRP51323B)；江苏省普通高校研究生实践创新计划项目(SJZZ_0148) |
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| 摘 要： | 针对人工蜂群算法在求解函数优化问题中存在收敛精度不高、收敛速度较慢的问题，提出了一种改进的增强寻优能力的自适应人工蜂群算法。该算法利用逻辑自映射函数产生混沌序列对雇佣蜂搜索行为进行混沌优化，并引入萤火虫算法中的自适应步长策略动态调整观察蜂的搜索行为，从而提升了算法的局部搜索能力。基于标准测试函数的仿真结果表明，改进后的人工蜂群算法在寻优精度和收敛速度上均有明显提高。
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| 关 键 词： | 人工蜂群算法 混沌优化 自适应步长策略 局部搜索 |
| 收稿时间： | 2015/5/24 0:00:00 |
| 修稿时间： | 2016/8/23 0:00:00 |
Adaptive artificial bee colony algorithm with enhanced search ability |
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| ZHANG Tai,TU Siyuan,WU Bin and GU Xiaofeng.Adaptive artificial bee colony algorithm with enhanced search ability[J].Application Research of Computers,2016,33(10). |
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| Authors: | ZHANG Tai TU Siyuan WU Bin and GU Xiaofeng |
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| Affiliation: | Key Laboratory of Advanced Process Control for Light Industry Ministry of Education,Department of Electronic Engineering,Jiangnan University,Wuxi,Key Laboratory of Advanced Process Control for Light Industry Ministry of Education,Department of Electronic Engineering,Jiangnan University,Wuxi,Key Laboratory of Advanced Process Control for Light Industry Ministry of Education,Department of Electronic Engineering,Jiangnan University,Wuxi, |
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| Abstract: | In order to overcome the drawbacks of low computational accuracy and slow convergence rate of conventional artificial bee colony (ABC) algorithm during solving the function optimization problems, the paper proposes a self-adaptive ABC algorithm with enhanced search ability. The modified algorithm used the logic self-mapping function to generate chaotic sequences so as to implement chaos optimization for the search behaviors of employed bees, and it adopted adaptive step strategy of firefly algorithm to dynamically adjust the search behaviors of observer bees, the approach improved the local search ability. Simulations based on standard testing functions indicate that the modified ABC algorithm exhibits obviously improved optimization accuracy and convergence rate. |
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| Keywords: | artificial bee colony algorithm local search chaos optimization adaptive step strategy of firefly algorithm |
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