An Improved Artificial Bee Colony Algorithm with History Best Points
作者单位：The Institute of Advanced Technology Nanjing University of Posts and Telecommunications College of Automation Nanjing University of Posts and Telecommunications Beijing Institute of Control Engineering
会议名称：《第30届中国控制与决策会议》
会议日期：2018年
学科分类：08[工学] 081104[工学-模式识别与智能系统] 0811[工学-控制科学与工程]
基 金：support from National Nature Science Foundation of China(No.61571236) the Macau Science and Technology Fund(FDCT 093/2014/A2,041/2017/A1) the Research Committee of University of Macau(MYRG2015-00011-FST,MYRG2015-00012-FST) Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX17_0795)
关 键 词：Artificial bee colony convergence rate evolutionary computation global search ability
摘 要：Depending on the power global search ability, artificial bee colony algorithm attracts more attentions in recent years. But its slow convergence rate constraints its development. To better balance its exploration and exploitation abilities, we define a new point named as mean history best points（MHB） to lead the direction of bee population. The numerical experiments on the basic benchmark functions validate the efficiency of our algorithm.