摘要
为解决公共自行车系统在交通高峰时间段自行车借还困难问题,提升公共自行车系统的运行效率和用户满意度,以某市的现有公共自行车系统运营情况为研究对象,通过大数据归纳了公共自行车系统的借用和返回规律,分析了公共自行车的运行特点,研究公共自行车的时间特性和周转特性,并且为调度模型的建立提供了数据基础,最后通过改进蚁群算法建立了较好的公共自行车调度模型。实验结果表明,建立的静态调度行驶路径优化模型得到了最优调度行驶路径,从而使高峰时间段自行车借还困难问题得到了有效解决,减少了调度所需时间并提高了工作效率。
In order to solve the problem of difficult to borrow bicycles during the rush hour of the public bicycle system,and improve the operating efficiency and user satisfaction of the public bicycle system,the operation of the existing public bicycle system in a certain city was used as the research object.The borrowing and return rules of the system analyze the operating characteristics of public bicycles,study the time characteristics and turnover characteristics of public bicycles,and provide a data basis for the establishment of scheduling models.Finally,a better public bicycle scheduling model is established through the ant colony algorithm.The ant colony algorithm,establishs a static dispatching route optimization model,and obtains the optimal dispatching route for dispatching vehicles.Thus,the problem of difficult to borrow bicycles during peak hours is effectively solved,reducing the time required for dispatching and improving work efficiency.
作者
李明明
LI Mingming(Management Center of Big Data and Network,Jilin University,Changchun 130025,China)
出处
《吉林大学学报（信息科学版）》
CAS
2020年第3期371-378,共8页
Journal of Jilin University（Information Science Edition）
关键词
公共自行车
调度模型
分布特征
周转特性
蚁群算法
public bicycles
scheduling model
distribution characteristics
turnaround characteristics
ant colony algorithm
