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一种应用于函数优化问题的多种群人工蜂群算法 预览 被引量:2

A Multi-swarm Artificial Bee Colony Algorithm for Function Optimization
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摘要 针对传统人工蜂群算法(ABC)收敛速度慢、易陷入局部最优解等不足,提出一种基于种群分割的多种群人工蜂群算法(MABC)应用于函数优化问题.该算法利用K均值聚类算法对蜂群进行种群分割,在子种群中引入基于全局通信的蜜源位置更新方式加速算法收敛,同时引入基于局部通信的适应度函数扩展解方案的多样性.通过对6个基准测试函数的实验表明,MABC算法适应度高、收敛速度快,克服了ABC算法易陷入局部最优解等不足,在函数优化问题中表现出了更好的性能. A multi-swarm Artificial Bee Colony(MABC)algorithm based on the segmentation of population was proposed in this paper.It was applied to function optimization to overcome the drawbacks of slow convergence and low computational accuracy of conventional ABC algorithm.In this algorithm,K-means clustering algorithm based on Euclidean distance was introduced to divide the bee colony.In the subpopulation,a method was introduced to update the location of nectar based on global communication to accelerate the convergence of the algorithm;and the fitness function based on local communication was introduced to expand the diversity of the solution.The simulation results of six standard functions showed that the MABC algorithm could attain significant improvement on convergence rate and solution accuracy,and show better performance in function optimization problems when compared with the ABC algorithm.
作者 王守娜 刘弘 高开周 WANG Shouna;LIU Hong;GAO Kaizhou(School of Information Science and Engineering,Shandong Normal University,Jinan 250014,China;Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology,Jinan 250358,China;Maritime Institute,Nanyang Technological University,Singapore 639798,Singapore)
出处 《郑州大学学报:工学版》 北大核心 2018年第6期30-35,共6页 Journal of Zhengzhou University: Eng Sci
基金 国家自然科学基金资助项目(61472232,61272094).
关键词 人工蜂群算法 种群分割 蜜源位置更新 适应度函数 函数优化 Artificial Bee Colony algorithm segmentation of population nectar location updating fitness function function optimization
作者简介 通信作者:刘弘(1955-),女,山东济南人,山东师范大学教授,博士,博士生导师,主要从事分布式人工智能领域研究,E-mail:lhsdcn@126.com.
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