计算机应用研究2016，Vol.33Issue(10)：2946-2948,2981,4.DOI:10.3969/j.issn.1001-3695.2016.10.016
增强寻优能力的自适应人工蜂群算法
Adaptive artificial bee colony algorithm with enhanced search ability
摘要
Abstract
In order to overcome the drawbacks of low computational accuracy and slow convergence rate of conventional artifi-cial bee colony (ABC)algorithm during solving the function optimization problems,this paper proposed a self-adaptive ABC algorithm with enhanced search ability.The modified algorithm used the logic self-mapping function to generate chaotic se-quences 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 optimiza-tion accuracy and convergence rate.关键词
人工蜂群算法/混沌优化/自适应步长策略/局部搜索Key words
artificial bee colony algorithm/chaos optimization/adaptive step strategy/local search分类
信息技术与安全科学引用本文复制引用
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):2946-2948,2981,4.基金项目
江苏省科技厅产学研联合创新资金资助项目（BY2013015-19）；中央高校基本科研业务费专项资金资助项目（JUSRP51323B）；江苏省普通高校研究生实践创新计划资助项目 （）
