计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (2): 60-60.

• 学术探讨 • 上一篇    下一篇

基于选路优化的改进蚁群算法

张毅,梁艳春   

  1. 吉林粮食高等专科学校计算机系
  • 收稿日期:2006-05-16 修回日期:1900-01-01 出版日期:2007-01-11 发布日期:2007-01-11
  • 通讯作者: 张毅 whdzy2000

An improved ant colony optimization algorithm based on route optimization

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  1. 吉林粮食高等专科学校计算机系
  • Received:2006-05-16 Revised:1900-01-01 Online:2007-01-11 Published:2007-01-11

摘要: 蚁群算法在处理大规模优化问题时效率很低。为此我们对蚁群算法提出了两点改进:(1)引入选路优化策略,减少了算法中蚂蚁的选路次数,显著提高了算法的执行效率。尤其对于以往较难处理的大规模TSP问题,改进算法在执行效率上有明显的优势。模拟实验结果表明改进算法较之基本蚁群算法在收敛速度有明显提高。

关键词: 蚁群算法, 旅行商问题, 选路策略, 并行策略, parallel strategy

Abstract: An improvement on Ant Colony Optimization (ACO) algorithm is presented in this paper. A novel optimized implementing approach is designed to reduce the processing costs involved with routing of ants in the conventional ACO. The results of the simulated experiments show that the improved algorithm not only reduces the number of routing in the ACO but also surpasses existing algorithms in performance for solving large-scale TSP problems. Simulations show that the speed of convergence of the improved ACO algorithm can be enhanced greatly compared with the traditional ACO.

Key words: Ant colony algorithm, traveling salesman problem