东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2012, Vol. 33 ›› Issue (9): 1240-1243+1252.DOI: -

• 论著 • 上一篇    下一篇

基于改进蚁群算法的双向物流路径优化

徐久强;邢佩龙;孔秋实;刘大鹏;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-19 修回日期:2013-06-19 出版日期:2012-09-15 发布日期:2013-04-04
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(61101121)

Logistics routing optimization based on improved ant colony algorithm

Xu, Jiu-Qiang (1); Xing, Pei-Long (1); Kong, Qiu-Shi (1); Liu, Da-Peng (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110819, China
  • Received:2013-06-19 Revised:2013-06-19 Online:2012-09-15 Published:2013-04-04
  • Contact: Xu, J.-Q.
  • About author:-
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摘要： 针对物流路径优化已有算法运算过程复杂、精度不高、过早收敛等问题,对蚁群算法进行了改进,以解决物流路径优化问题.为了消除蚁群算法的易停滞、收敛慢等问题,从蚂蚁转移策略、信息素更新方式以及遗传算法的融合等方面对算法进行了改进.针对双向物流的路径优化问题,通过增加启发函数、设计转移策略等方面来改进蚁群算法,使得算法能更好地考虑综合因素来进行搜索,能够更全面、更准确地找到合适的下一节点,从而得到更优的路线.

关键词: 物流路径优化, 蚁群算法, 启发函数, 转移策略, 双向物流路径

Abstract: Due to computation complexity, lower accuracy and premature convergence of the conventional algorithm, the ant colony algorithm was improved to solve the routing problem of logistics. In order to eliminate the problems that ant colony algorithm is easy to be stagnant and its convergence is slow, the algorithm was improved including the following points such as the transfer strategies of the ants, the pheromone update method and the integration of genetic algorithm. To solve the path optimization of simultaneous delivery and pickup, the heuristic function was added and the transfer strategies were designed, which made the algorithm conduct a search by considering a combination of factors reasonably, and could find the next right point more comprehensively and more accurately, then, a better path could be gotten.

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