城市故障共享单车回收路径优化——以摩拜单车为例

为保障用户骑行安全及企业正常运维,需要及时回收故障共享单车,科学规划回收路径从而提高回收效率.首先,在简要分析故障共享单车回收现状的基础上,对其进行定义和分类,并确定回收准则及具体流程其次,选择K-means算法对故障共享单车进行聚类处理,构建以回收工作总成本最低为目标的路径优化模型最后,以上海市徐汇区部分区域的故障摩拜单车为例,设计改进蚁群算法进行求解,验证了所用模型和算法的正确有效性研究表明:满载率系数与回收车辆行驶用时呈正相关性,服务节点个数同时影响着搬运时间和行驶时间,从而对回收总成本产生较大影响因此在安排回收任务时,企业应结合现实情况的工作量及计划成本来选择具体参数,使得模型更贴合实际规划需求.

Optimization of Recycling Route of City Unusable Sharing Bicycles:Taking Mobike as an Example

In order to ensure the riding safety of users and the normal operation and maintenance of enterprises, it is necessary to recover the unusable sharing bicycles in time, and scientifically plan the recovery path to improve the recovery efficiency. Based on a brief analysis of the current situation of recycling, the unusable sharing bicycles are defined and classified, and the recycling criteria and specific procedures are determined. Next, the K-means algorithm is chosen to cluster the unusable sharing bicycles. A path optimization model with the lowest total cost of recovery work as the goal was constructed, and an improved ant colony algorithm was designed to solve the problem by taking the faulty Mobike bicycles in some areas of Xuhui District, Shanghai as an example, and the correctness and effectiveness of the models and algorithms used were verified. Research has shown that the full load factor is positively correlated with the travel time of recycled vehicles, and the number of service nodes affects both the transport time and travel time, which has a significant impact on the total cost of recycling. Therefore, when arranging recovery tasks, companies should take into account the real situation of the workload and planning costs to select specific parameters, so that the model more closely matches the actual planning needs.