计算机工程2012，Vol.38Issue(18)：182-185,4.DOI:10.3969/j.issn.1000-3428.2012.18.049
基于优胜劣汰规则的异类多种群蚁群算法
Heterogeneous Multiple Colonies Ant Colony Algorithm Based on Survival of Fittest Rules
摘要
Abstract
A Heterogeneous Multiple Ant Colony algorithm based on Survival of Fittest rules(HMACSF) is presented. This algorithm introduces more than one type of ant colony. All types of ant colonies with different pheromone updating mechanism and searching traits have mutual compensation of advantages, as well as mutual competitive exclusion. According to the results of the exchanging, HMACSF retains the dominant colonies, weeds out the inferiors, and improves the solving efficiency and diversity of solutions, to easily converge the global optimal solution. A series of Traveling Salesman Problem(TSP) experiments show that this algorithm can generate solutions with better quality and faster speed.关键词
蚁群/优胜劣汰规则/蚁群算法/旅行商问题/合作规则/竞争规则Key words
ant colony/ survival of fittest rules/ ant colony algorithm/ Traveling Salesman Problem(TSP)/ collaboration rule/ competition rule分类
信息技术与安全科学引用本文复制引用
张鹏,魏云霞,薛宏全,王永忠..基于优胜劣汰规则的异类多种群蚁群算法[J].计算机工程,2012,38(18):182-185,4.基金项目
西安市科技计划基金资助项目“基于智能视频行为识别的城市公共安全决策支持系统研究”(CXY11191(4)) （CXY11191(4）
