基于改进ACO的战后物资回收车辆路径优化  

Vehicle Path Optimization for Post-war Material Recovery Based on Improved ACO

作　　者：孟小玲 温海骏[1] 曾艾婧 邵延君[1] MENG Xiao-ling;WEN Hai-jun;ZENG Ai-jing;SHAO Yan-jun(North University of China,Taiyuan 030051,China)

机构地区：[1]中北大学,太原030051

出　　处：《火力与指挥控制》2020年第9期47-51,共5页Fire Control & Command Control

基　　金：山西省自然科学基金资助项目(201701D121079,201801D121185);山西省研究生创新资助项目(2020SY349)。

摘　　要：针对战后军事基地遗留的武器装备回收的车辆最短路径和运输成本最低的问题,考虑到基本蚁群算法容易陷入局部寻优的缺陷,提出了一种适用于求解路径优化的改进蚁群算法,构建了新的概率模型和信息素更新模型。结果表明,改进后的蚁群算法在寻优能力、可靠性及收敛效果、稳定性方面都优于基本蚁群算法,为战后军事物资回收再制造的车辆路径物流问题提供了一种新的优化途径。In view of the problem of the shortest path and the lowest transportation cost of the vehicles recovered from the weapons and equipment left over from the postwar military bases,and considering the defect that the basic ant colony algorithm is prone to fall into local optimization.An improved ant colony algorithm suitable for solving path optimization is proposed,and a new probability model and pheromone updating model are constructed.The results show that the improved ant colony algorithm is superior to the basic ant colony algorithm in optimization ability,reliability,convergence effect and stability.It provides a new optimized way for the vehicle route logistics of the post-war military material recycling and remanufacturing.

关 键 词：武器装备回收 改进蚁群算法 车辆路径优化 运输成本 

分 类 号：TJ01[兵器科学与技术—兵器发射理论与技术]