摘要
为了解决共享单车投放点选址问题,本文将建立投放点车辆预测需求模型预测小区总投放数量,同时构建投放点选址模型,并结合实际数据利用蚁群算法寻求最优解。算例结果表明,模型与算法能有效地确定服务小区内共享单车投放点位置、数量及投放车辆总数,解决服务小区间调配问题中存在的选址难题。
To solve the bicycle-sharing location problem, in this study, a vehicle-demand forecasting model is established to predict the total number of drop-in areas. A location model of the drop-in point is constructed, and the optimal solution is found by using an ant colony optimization algorithm combined with actual data. The results show that the model and algorithm can effectively determine the location and quantity of vehicles placed in the service area, and solve the problem of location selection in the allocation of service areas.
作者
叶锦程
赵怀明
胡骥
YE Jin-chen;ZHAO Huai-ming;HU Ji(School of Transportation and Logistics,Southwest Jiaotong University,Chengdu 610031,China;China Railway Eryuan Engineering Group Co. Ltd,Traffic Regulation Institute,Chengdu 610081,China)
出处
《交通运输工程与信息学报》
2019年第1期45-51,共7页
Journal of Transportation Engineering and Information
关键词
城市交通
投放点
选址模型
共享单车
蚁群算法
urban traffic
delivery point
location model
shared bicycle
ant colony optimization algorithm
