计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (28): 81-83.

• 学术探讨 • 上一篇    下一篇

嵌入混和混沌搜索的蚁群算法

金 雁1,2,赵 耀2   

  1. 1.华中科技大学 交通学院,武汉 430074
    2.武汉理工大学 交通学院,武汉 430063
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-10-01 发布日期:2007-10-01
  • 通讯作者: 金 雁

Ant colony algorithms with hybrid chaos searching

JIN Yan1,2,ZHAO Yao2   

  1. 1.School of Transportation,Huazhong University of Science and Technology,Wuhan 430074,China
    2.School of Transportation,Wuhan University of Technology,Wuhan 430063,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-10-01 Published:2007-10-01
  • Contact: JIN Yan

摘要: 介绍了一种嵌入变尺度方法和禁忌搜索的混沌优化的蚁群优化法(ACA-HCO),通过产生随机性的混沌变量,加入智能性禁忌表,采用变尺度法,加速搜索过程,混沌变量的随机性和遍历性有效克服了基本蚁群算法陷入局部最优的不足。将此方法用于求解C-TSP问题结果令人满意,用此方法进行数值计算,并与混和混沌法(MSCOA-TB)比较,其效果明显高于MSCOA-TB。

关键词: 蚁群算法, 混和混沌, 优化, 信息素

Abstract: The text introduces an Ant Colony Algorithms with Hybrid Chaos Optimization(ACA-HCO),which speed the searching by producing a lot of chaos variables randomly,joining the intelligent taboo forms,and adopting multiple scales searching.The chaos random variables can conquer the basic ACA’s weakness of sinking in local optimization.Using this algorithms to solve the famous CTSP and four common test functions,the results are satisfying.

Key words: ant colony algorithms, hybrid chaos, optimization, pheromone