纺织高校基础科学学报Issue(4)：512-517,6.
基于随机搜索变异策略的人工蜂群算法
Random mutation artificial bee colony algorithm
张伟1
作者信息
- 1. 西安电子科技大学数学与统计学院，陕西西安710126
- 折叠
摘要
Abstract
Aiming at the shortcoming of artificial bee colony algorithms ,such as the low convergence rate and easy to be trapped into the local optimums ,an improved ABC algorithm with random mutation ———RMABC algorithm is proposed .First ,random choice method was adopted to implement mutation and disturbance operation ,which was aimed at increasing the diversity of population and balancing the local and global search .T hen ,in order to enhance the global convergence speed ,the search strategy of scout bees was changed .A food source which cannot be further improved through a predetermined trials of limit times was replaced with opposite food source .Experiments are conducted on a set of 9 benchmark functions .The results demonstrate the RMABC algorithm has a faster convergence rate and higher solu‐tion accuracy ,and show s good performance in solving complex numerical optimization problems .关键词
人工蜂群算法/随机搜索/搜索方程/函数优化Key words
artificial bee colony algorithm/dynamic random mutation/search equation/function optimi-zation分类
信息技术与安全科学引用本文复制引用
张伟..基于随机搜索变异策略的人工蜂群算法[J].纺织高校基础科学学报,2014,(4):512-517,6.
