计算机应用研究2018，Vol.35Issue(3)：658-660,704,4.DOI:10.3969/j.issn.1001-3695.2018.03.004
求解连续空间优化问题的改进蜂群算法
Modified artificial bee colony algorithm for solving continuous space optimization problems
摘要
Abstract
This paper proposed a modified artificial bee colony algorithm to tackle the dilemma of easily trapping in local optimum in original artificial bee colony.Firstly,it applied an opposition-based learning method for the initial population generation,which aimed to improve the quality of initial solutions.Meanwhile,it employed the estimation of distribution metaheuristic to established the probability model of solution domain about good individuals for neighbor search.This operation was capable of improving the searching performance and avoiding local optimum.Finally,it conducted the simulations to tackle the continuous space optimization problems.The experimental results demonstrate that the modified algorithm has fast constringency speed and the global optimization capability is enhanced.关键词
人工蜂群算法/连续空间优化/反向学习/分布估计算法Key words
artificial bee colony (ABC) algorithm/continuous space optimization/opposition-based learning/estimation of distribution algorithm(EDA)分类
信息技术与安全科学引用本文复制引用
王永琦,吴飞,孙建华..求解连续空间优化问题的改进蜂群算法[J].计算机应用研究,2018,35(3):658-660,704,4.基金项目
国家自然科学基金资助项目(F020207) （F020207）
上海市科委资助项目(13510501400) （13510501400）
上海市工程技术大学《信号与系统》平台课程建设项目(k201602004) （k201602004）
