基于自适应动态重组和极值扰动的人工蜂群算法  

Artificial Bee Colony Algorithm Based on Adaptive Dynamic Reconfiguration and Extremum Disturbance

作　　者：倪红梅[1] 刘永建[2] 李盼池[1] NI Hongmei;LIU Yongjian;LI Panchi(School of Computer and Information Technology,Northeast Petroleum University,Daqing 163318,Heilongjiang Province,China;School of Petroleum Engineering,Northeast Petroleum University,Daqing 163318,Heilongjiang Province,China)

机构地区：[1]东北石油大学计算机与信息技术学院,黑龙江大庆163318 [2]东北石油大学石油工程学院,黑龙江大庆163318

出　　处：《吉林大学学报（理学版）》2019年第3期607-612,共6页Journal of Jilin University:Science Edition

基　　金：国家自然科学基金(批准号:61170132);国家科技重大专项基金(批准号:2016ZX05012-001);东北石油大学培育基金(批准号:NEPUPY120224)

摘　　要：针对人工蜂群算法存在寻优能力弱和收敛速度慢的问题,提出一种基于自适应动态重组和极值扰动的人工蜂群算法.首先通过引入混沌优化算子产生初始解,根据雇佣蜂的贡献度对其进行自适应动态重组,然后引入极值扰动算子对雇佣蜂个体极值和全局最优值实施随机扰动.实验结果表明,该算法增加了种群的多样性,加快了算法收敛速度,提高了种群的可进化能力.Aiming at the problems of weak optimization ability and slow convergence speed of artificial bee colony algorithm, we proposed an artificial bee colony algorithm based on adaptive dynamic reconfiguration and extremum disturbance. First, we introduced chaos optimization operator to generate initial solutions and carry out adaptive dynamic reconfiguration according to the contribution of hired bees. Then, we introduced extremum disturbance operator to implement random perturbation to the individual extreme value and global optimal value of hired bees . The experimental results show that the algorithm increases the diversity of the population, accelerates the speed of convergence, and improves the evolutionary ability of population.

关 键 词：人工蜂群算法 混沌优化算子 贡献度 自适应动态重组 极值扰动 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]