计算机工程Issue(11)：189-193,5.DOI:10.3969/j.issn.1000-3428.2014.11.037
基于多维贪婪搜索的人工蜂群算法
Artificial Bee Colony Algorithm Based on Multi-dimensional Greedy Search
摘要
Abstract
Artificial Bee Colony ( ABC ) algorithm can be efficiently employed to solve the multimodal and high dimensional function optimization problem. However,low search speed and premature convergence frequently appear with more complex problem. In order to improve the algorithm performance,this paper proposes a new artifciall bee colony algorithm . It introduces a search equation based on multi-dimensional greedy search to enhance local search and avoid the solution to be abandoned which achieves optimum value in some dimensions but reach the maximum update limit. New algorithm also adds a disturbance mechanism to avoid obtaining partial optimal solutions when premature convergence in a few dimensions. Experimental results show the new algorithm can balance the exploitation and exploration,has more fast convergence speed and better computational precision in solving the multimodal and high dimensional function optimization problem.关键词
人工蜂群算法/函数优化/贪婪搜索/扰动搜索/深度挖掘/广度搜索Key words
Artificial Bee Colony( ABC) algorithm/function optimization/greedy search/disturbance search/depth excavation/scope search分类
信息技术与安全科学引用本文复制引用
张素琪,滕建辅,顾军华..基于多维贪婪搜索的人工蜂群算法[J].计算机工程,2014,(11):189-193,5.基金项目
天津市应用基础与前沿技术研究计划基金资助重点项目(13JCZDJC26300)。 （13JCZDJC26300）
