期刊文献+

基于混沌技术的蚁群混合优化方法 被引量:3

Hybrid algorithm for ant colony optimization based on chaos technology
在线阅读 下载PDF
导出
摘要 为提高蚁群优化算法的求解性能,在分析了处理连续变量的蚁群优化算法的基础上,给出了两种混沌映射的映射规则,并构建了基于Logistic映射的混沌蚁群优化方法(LM-ACO)以及基于Henon映射的混沌蚁群优化方法(HM-ACO),给出了k次均方根包络函数简化及平滑多约束条件的处理方法。采用LM-ACO、HM-ACO以及蚁群处理连续变量的优化方法分别对机械有约束优化实例进行求解,在求解过程中,从各种方法获得的最优解、成功率指标、平均有效迭代数、迭代占用时间等方面作对比。比较结果表明:采用基于Henon映射的蚁群混合优化方法具有求解精度高、优化效率高等优点。 In order to improve the solving performance of Ant Colony Optimization(ACO),firstly the ACO method which deals with the optimal problem with continuous variable is analyzed and mapping rules for two types of chaos map are given.Next,ACO based on Logistic Map(LM-ACO) and Henon Map(HM-ACO) are constructed,and the method which adopts k mean-square-root envelope function to reduce and smooth multi-constraints is given.To compare the performance of LM-ACO,HM-ACO and the ACO,the three methods are used to solve the pressure vessel constrained optimal problem.Their performances are compared in terms of optimal solution,success ratio,average valid evaluation number,iterative occupancy hours and so on.Comparison results indicate that the HM-ACO has many advantages such as higher solution accuracy and higher computational efficiency
出处 《计算机工程与应用》 CSCD 北大核心 2011年第13期42-45,102,共5页 Computer Engineering and Applications
基金 河南省科技计划项目(No.112300410234) 河南省教育厅青年骨干教师计划项目(No.2009GGJS-075) 河南省教育厅自然基础计划资助项目(No.2010A520034)
关键词 Logistic映射:Henon映射 混沌 蚁群优化 Logistic map Henon map chaos ant colony optimization
  • 相关文献

参考文献9

二级参考文献36

  • 1谯春,程熹,舒达.张紧弦振动的频率偏移[J].物理实验,2005,25(4):45-48. 被引量:8
  • 2方天申.弦n维振动的模糊关系矩阵描述方法[J].安徽大学学报(自然科学版),2005,29(3):42-45. 被引量:3
  • 3方明强.对弹性弦非小振幅振动的初步分析[J].力学与实践,2005,27(6):73-74. 被引量:2
  • 4舒服华.基于蚁群算法的饲料螺旋输送机优化设计[J].饲料工业,2006,27(15):1-4. 被引量:13
  • 5Bilchev G, Parmee I C. The ant colony metaphor for searching continuous design spaces. Lecture Notes in Computer Science, LNCS 993, Berlin, Germany: Springer-Verlag, 1995:25-39
  • 6Mathur M, Karale S B, Priyee S, et al. Ant colony approach to continuous function optimization. Industral Engineering Chemistry Research, 2000, 39(10): 3814-3822
  • 7Dreo J, Siarry P. A new ant colony algorithm using the hierarchical concept aimed at optimization of multi-minima continuous functions. Lecture Notes in Computer Science, LNCS 2463, Berlin, Germany: Soringer-Verlag, 2002:216-221
  • 8Li L X, Peng H P, Wang X D, et al. An optimization method inspired by chaotic ant behavior. International Journal of Bifurcation and Chaos, 2006, 16(8): 2351-2364
  • 9Li Y Y, Li L X, Wen Q Y, et al. Data fitting via chaotic ant swarm. Proceedings of 2nd International Conference on Natural Computation, Sep 24-27 2006, Xi'an, China. Berlin, Germany: Springer-Verlag, 2006: 180-183
  • 10Li Y Y, Li L X, Wen Q Y, et al. Integer programming via chaotic ant swarm. The 3rd International Conference on Natural Computation: Vol 4,Aug 24-27 2007, Haikou, China. Berlin, Germany: Springer-Verlag, 2007:489-493

共引文献24

同被引文献20

引证文献3

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部