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计算机工程 ›› 2012, Vol. 38 ›› Issue (18): 182-185. doi: 10.3969/j.issn.1000-3428.2012.18.049

• 人工智能及识别技术 • 上一篇    下一篇

基于优胜劣汰规则的异类多种群蚁群算法

张 鹏 1,魏云霞 2,薛宏全 1,王永忠 3   

  1. (1. 西安理工大学经济与管理学院,西安 710048;2. 陕西省银行学校财经商贸部,西安 710065;3. 内蒙古兰太实业股份有限公司,内蒙古 阿拉善盟 750336)
  • 收稿日期:2011-10-08 修回日期:2012-01-11 出版日期:2012-09-20 发布日期:2012-09-18
  • 作者简介:张 鹏(1975-),男,讲师、博士,主研方向:智能算法,决策支持系统,人工智能;魏云霞,硕士;薛宏全,讲师、博士研究生;王永忠,工程师
  • 基金资助:
    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))

Heterogeneous Multiple Colonies Ant Colony Algorithm Based on Survival of Fittest Rules

ZHANG Peng 1, WEI Yun-Xia  2, XUE Hong-quan 1, WANG Yong-zhong 3   

  1. (1. College of Economic and Management, Xi’an University of Technology, Xi’an 710048, China; 2. Department of Finance and Commerce, Shaanxi Banking School, Xi’an 710065, China; 3. Inner Mongolia Lantai Industry Co., Ltd., Alashanmeng 750336, China)
  • Received:2011-10-08 Revised:2012-01-11 Online:2012-09-20 Published:2012-09-18

摘要: 提出一种基于优胜劣汰规则的异类多种群蚁群算法,该算法由多类不同特性的蚁群构成,彼此间具有潜在的合作性和对抗性。根据蚁群间定期信息交换的结果,引入自然界优胜劣汰准则,设定蚁群间的合作规则、竞争规则、裂变规则。以旅行商问题为例进行相关实验和比较。通过多个种群间的相互合作与竞争,保留优势种群,淘汰劣势种群,提高求解效率,改善解的多样性,使算法更容易收敛到全局最优解。

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

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.

Key words: ant colony, survival of fittest rules, ant colony algorithm, Traveling Salesman Problem(TSP), collaboration rule, competition rule

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