江西科学2017，Vol.35Issue(2)：242-246,5.DOI:10.13990/j.issn1001-3679.2017.02.012
改进的人工蜂群算法
Improved Artificial Bee Colony Algorithm
摘要
Abstract
Artificial bee colony algorithm is a new group of intelligent optimization algorithm,with its unique optimization mechanism is widely used.However,this algorithm has the shortcomings of "early maturing" convergence and poor search ability in late evolution.In view of this problem,we use the method of initial learning of reverse learning and introduce the search equation inspired by differential evolution algorithm,and propose an improvement Artificial Bee Colony Algorithm (abbreviated as DEABC).Simulation results of five test functions are compared with other algorithms.The results show that the DEABC algorithm has better optimization efficiency and optimization performance.关键词
人工蜂群算法/差分进化算法/种群初始化/搜索方程Key words
artificial bee colony/differential evolution algorithm/population initialization/search equation分类
信息技术与安全科学引用本文复制引用
郝继升,井文红,任浩然..改进的人工蜂群算法[J].江西科学,2017,35(2):242-246,5.基金项目
陕西省高水平大学建设专项资金资助项目(2012SXTS06) （2012SXTS06）
延安市科技局项目(2014ZC-6). （2014ZC-6）
