基于改进蚁群算法的B2B城配模式下车辆路径优化  

Vehicle Routing Optimization under B2B Urban Distribution Mode Based on Improved Ant Colony Algorithm

作　　者：陈志新[1] 闫昊炜 张昕宇 张志浩 CHEN Zhi-xin;YAN Hao-wei;ZHANG Xin-yu;ZHANG Zhi-hao(School of Logistics,Beijing Wuzi University,Beijing 101149,China)

机构地区：[1]北京物资学院物流学院,北京101149

出　　处：《公路交通科技》2023年第7期231-238,共8页Journal of Highway and Transportation Research and Development

基　　金：北京物资学院校级科研项目(2021XJKY15);北京市自然科学基金项目(3173043);北京市教委科研计划一般项目(KM201810037003)。

摘　　要：考虑到物流城配企业在制订高效配送方案时需要更优化的车辆路径,提出了一种改进的蚁群算法并将其应用于城市B2B模式下车辆配送的路径优化。针对传统蚁群算法中只考虑收货点之间的距离和路径上的信息素浓度对状态转移概率公式的影响,而没有考虑从蚂蚁转移后的位置返回配送中心的距离,路径上的信息素浓度过高而导致寻优陷入局部最优解,或因为路径上的信息素浓度过低而影响算法收敛和寻优效率,对所有蚂蚁遍历完所有待访问的收货点后搜索到的所有路径上的信息素进行更新而导致算法收敛和计算效率降低等缺陷,改进了算法中的状态转移概率公式、优化了信息素浓度设定和更新方式,设计了改进蚁群算法的实现步骤。配送线路的安排是决定配送成本、准时性、效益等配送水平高低的关键。以某城市的啤酒配送中心业务为例,建立了B2B城配模式下的车辆配送路径优化模型并求解,验证了改进算法的可行性及有效性。将改进蚁群算法与基本蚁群算法进行了多次对比试验。结果表明:改进蚁群算法求得的最优解的路径长度和取得最优解的概率都优于基本蚁群算法;原调度系统根据订单数据调用改进算法,能实现配送和运输成本最低的车辆调度,为配送车辆提供最佳配送路线,并调用百度地图将智能规划的各车辆的最优配送路径进行可视化展示。Considering that logistics urban distribution enterprises need more optimized vehicle routing when formulating efficient distribution schemes,an improved ant colony algorithm is proposed and applied to vehicle distribution routing optimization under urban B2B mode.In the traditional ant colony algorithm,only the influence of the distance between the receiving points and the pheromone concentration on the path on the state transition probability formula is considered,but the distance from the location transferred by ant to the distribution center is not considered,the pheromone concentration on the path is too high,resulting in the optimization falling into the local optimal solution,or the algorithm convergence and optimization efficiency are affected because the pheromone concentration on the path is too low,and the algorithm convergence and calculation efficiency are reduced by updating all pheromone on the path searched by all ants after they traversed all the receiving points to be visited.In view of these defects,the state transition probability formula in the algorithm is improved,the pheromone concentration setting and updating mode are optimized,and the implementation steps of the improved ant colony algorithm are designed.The arrangement of distribution route is the key to determine the distribution level such as distribution cost,punctuality and benefit.Taking the business of beer distribution center in a city for example,the vehicle distribution route optimization model under B2B urban distribution mode is established and solved,and the feasibility and effectiveness of the improved algorithm are verified.The improved ant colony algorithm is compared with the traditional ant colony algorithm for many times.The result shows that(1)the path length and probability of obtaining the optimal solution obtained by the improved ant colony algorithm are better than those of traditional ant colony algorithm;(2)the original scheduling system calls the improved algorithm according to the order data,which can realize

关 键 词：物流工程 路径优化 改进蚁群算法 车辆调度系统 B2B模式 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] U495[自动化与计算机技术—计算机科学与技术]