作者投稿和查稿 主编审稿 专家审稿 编委审稿 远程编辑

计算机工程 ›› 2009, Vol. 35 ›› Issue (8): 34-37. doi: 10.3969/j.issn.1000-3428.2009.08.012

• 博士论文 • 上一篇    下一篇

面向TSP求解的混合蚁群算法

张 泓,李爱平,刘雪梅   

  1. (同济大学现代制造技术研究所,上海 200092)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-04-20 发布日期:2009-04-20

Hybrid Ant Colony Algorithm for TSP

ZHANG Hong, LI Ai-ping, LIU Xue-mei   

  1. (Institute of Advanced Manufacturing Technology, Tongji University, Shanghai 200092)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-04-20 Published:2009-04-20

摘要: 针对蚁群算法的早熟和停滞等现象,将免疫算法机制引入蚁群算法,提出用于TSP求解的混合算法。该算法具有蚁群算法的自适应反馈机理、收敛速度快和免疫算法操作算子简单和维持种群多样性、防止种群退化等特性。从算法解的质量与效率方面与基本蚁群算法和免疫算法进行比较,结果表明融合免疫机制的蚁群算法性能显著提高,也为解决其他组合优化问题提供一个新的思路。

关键词: 蚁群算法, 免疫算法, 旅行商问题, 混合算法

Abstract: Aiming at the phenomena such as precocity and stagnation of ant colony algorithm, the mechanism of immunity algorithm is put into ant colony algorithm. This paper presents a new hybrid algorithm absorbed the adaptive feedback mechanism and fast convergence merits of ant colony algorithm and simple operation operators and keeping diversity of groups without degenerating merits of immunity algorithm. The new hybrid algorithm is compared with basic ant colony algorithm and immunity algorithm from the aspects of solution quality and algorithm efficiency. Results show that the new hybrid algorithm performance is improved markedly. It also provides a new idea for solving other combinational optimization problems.

Key words: Ant Colony Algorithm(ACA), Immunity Algorithm(IA), Traveling Salesman Problem(TSP), hybrid algorithm

中图分类号: