计算机工程与应用 ›› 2015, Vol. 51 ›› Issue (2): 255-258.

• 工程与应用 • 上一篇    下一篇

两阶段式的物流配送路径优化方法

蒋国清1,潘  勇2,胡飞跃1   

  1. 1.长沙民政学院 软件学院,长沙 410004
    2.中南大学 地学与环境工程学院,长沙 410083
  • 出版日期:2015-01-15 发布日期:2015-01-12

Research on logistics distribution route based on genetic algorithm and ant colony optimization algorithm

JIANG Guoqing1, PAN Yong2, HU Feiyue1   

  1. 1.School of Software, Changsha Social Work College, Changsha 410004, China
    2.School of Geosciences and Environmental Engineering, Central South University, Changsha 410083, China
  • Online:2015-01-15 Published:2015-01-12

摘要: 根据组合优化理论,充分利用遗传算法、蚁群算法的优化点,提出了一种两阶段式的物流配送路径优化方法(GA-ACO)。利用遗传算法迅速找到物流配送路径优化问题的初始解,初始解生成蚁群算法的初始信息素分布,通过蚁群算法找到物流配送路径的最优方案。采用实例对GA-ACO的性能进行测试,测试结果表明,GA-ACO可以获得较好的物流配送路径优化方案,是一种高效率、鲁棒性好的物流配送路径优化问题求解方法。

关键词: 物流配送, 路径优化, 蚁群算法, 遗传算法, 组合优化理论

Abstract: According to the combination optimization theory and to make full use of optimization genetic algorithm and ant colony algorithm, this paper puts forward a novel method of logistics distribution route optimization based on genetic algorithm and ant colony optimization algorithm. The mathematical model of logistics distribution route optimization problem is established, and then genetic algorithm which has the global optimization search ability is used to find the feasible scheme of logistics distribution route, the feasible scheme of the genetic algorithm is taken as the initial solution of the ant colony algorithm, the behavior of ant foraging is simulated to find the optimal solution of logistics distribution route. The performance of the proposed method is tested by simulation experiments, test results show that the proposed method can obtain better optimization scheme of logistics distribution route, is a high efficiency and robustness optimization method to solve logistics distribution routing problem.

Key words: logistics distribution, routing optimization, ant colony optimization algorithm, genetic algorithm, combination optimization theory