物流配送车辆路径规划研究

Changhao Piao, Hao Hu, Yan Zhang
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引用次数: 2

摘要

针对物流配送中的车辆路径问题,提出了一种改进的蚁群优化算法。在配送过程中,缩短配送里程使路径引入最小化。通过建立相应的matlab分布模型,采用改进的蚁群算法求解最优路径。改进蚁群算法根据搜索阶段设置波动因子,并在启发式因子中考虑起始点、终点和各节点之间的距离。实验结果表明,与传统的人工方案相比,采用了物流配送路径规划模型和改进的蚁群算法,有效地减少了物流配送作业路径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Logistics distribution vehicle path planning research
Aiming at the problem of vehicle routing in logistics distribution, an improved ant colony optimization algorithm was proposed. In the distribution process, shortening the delivery mileage minimizes the path Introduction. By establishing a corresponding matlab distribution model, an improved ant colony algorithm is used to solve the optimal path. The improved ant colony algorithm sets the volatility factor according to the search stage, and considers the starting point, the end point and the distance between each node in the heuristic factor. The experimental results show that compared with the traditional manual scheme, the logistics distribution path planning model and the improved ant colony algorithm are adopted to effectively reduce the logistics distribution operation path.
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