Improving Chaotic Ant Swarm Performance with Three Strategies

摘要：

　　This paper presents an improved chaotic ant swarm (ICAS) by introducing three strategies, which are comprehensive learning strat egy, search bound strategy and refinement search strategy, into chaotic ant swarm (CAS) for solving optimization problems.The first two strate gies are employed to update ants positions, which preserve the diversity of the swarm so that the ICAS discourages premature convergence.In addition, the refinement search strategy is adopted to increase the solu tion quality in the ICAS.Simulations show that the ICAS significantly enhances solution accuracy and convergence stability of the CAS.

作者: Yu-Ying Li Li-Xiang Li Hai-Peng Peng

作者单位: Basis Department Institute of Chemical Defense of the Chinese Peoples Liberation Army,Beijing, 1022 Information Security Center,Beijing University of Posts and Telecommunications,Beijing, 100876, Chin

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 268-277

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）