文献类型：期刊文献

中文题名：一种快速自适应蜂群算法及其应用

英文题名：A Quick Self-Adaptive Artificial Bee Colony Algorithm and Its Application

作者：何鹏[1];阎兴頔[1];侍洪波[1]

机构：[1]华东理工大学信息科学与工程学院,上海200237

年份：2013

卷号：39

期号：5

起止页码：588

中文期刊名：华东理工大学学报（自然科学版）

外文期刊名：Journal of East China University of Science and Technology

收录：CSTPCD;;Scopus;北大核心:【北大核心2011】；CSCD:【CSCD2013_2014】；

语种：中文

中文关键词：人工蜂群;自适应;搜索进程;函数优化

外文关键词：artificial bee colony; self-adaptive; search process; function optimization

摘要：人工蜂群算法(Artificial Bee Colony,ABC)具有操作简单、控制参数少及鲁棒性强等特点,已成为群体智能领域的研究热点之一,但其仍然存在收敛速度慢、易陷入局部最优的问题。针对这些问题,提出了一种改进的人工蜂群算法(Quick Self-Adaptive Artificial Bee Colony,QAABC)。首先,对人工蜂群算法的选择策略和搜索策略进行改进,以提高算法的收敛速度和优化精度;其次,对超边界的个体进行一次有效变异,增强种群的多样性。最后,将本文算法与其他两种算法(标准ABC、ABCP)对5个测试函数在低维和高维进行了对比实验,并将之运用于压力容器设计中成本最小化问题的研究,所得结果均验证了改进算法的有效性。
Due to its simpler operation, less control parameters, and stronger robustness, artificial bee colony algorithm （ABC） has been Becoming a hot topic of swarm intelligence. However, there still exist some shortcomings in ABC algorithm, such as low convergence rate and easily falling into local optimization. Hence, this paper proposes a quick self-adaptive artificial bee colony algorithm （QAABC）. First, the strategies of selection and search in the standard ABC are improved to enhance the convergence rate and the optimization precision. Then, in order to maintain the population diversity, an effective mutation is utilized when the particles beyond the boundary. Finally, the comparisons between the proposed approach with other algorithms, Standard ABC and ABCP, are made on 5 test functions. Moreover, the QAABC algorithm is also applied to the minimization of the cost in the pressure vessel design. The above experiments show the effectiveness of the improved algorithm.