摘要
针对工作日共享汽车租赁点处车辆供需不平衡问题,基于共享汽车运营商效益对共享汽车站点规模进行研究。以共享汽车企业利润为研究目标,以共享汽车站点规模为研究对象,在对工作日实际居民出行数据挖掘和热点出行区域分析的基础上,构建共享汽车租赁点建设规模模型,分别选取精确算法与启发式算法求解模型,并对算法结果进行对比。研究结果表明,文中所提出的租赁点建设规模模型及启发式算法具有准确性和时效性。该方法对共享汽车企业制定租赁点建设规划策略,完善共享汽车选址规模理论和提高资源利用率具有一定的理论意义和实际价值。
Aiming at the problem of imbalance between supply and demand of shared car rental locations on weekdays,the scale of shared car sites was studied based on the benefits of shared car operators.We took the profit of car-sharing companies as the research goal and the scale of car-sharing sites as the research object.Based on the data of actual residents’trips on weekdays and the analysis of hot travel areas,a model of the scale of construction of shared car rental sites was constructed,Then the exact algorithm and memetic algorithm were selected to solve this problem respectively.We also solved the model with heuristic algorithm,and compared the results of the algorithm.The experimental results show that the construction scale model and heuristic algorithm proposed in this paper have accuracy and timeliness.This method has certain theoretical significance and practical value for car-sharing companies to formulate lease site construction planning strategies,improving the theory of shared car site selection scale and resource utilization.
作者
翟榕真
李文权
郑文
张晨皓
ZHAI Rong-zhen;LI Wen-quan;ZHENG Wen;ZHANG Chen-hao(School of Transportation,Southeast University,Nanjing 210096,China)
出处
《武汉理工大学学报》
CAS
2021年第7期36-41,47,共6页
Journal of Wuhan University of Technology
基金
江苏省研究生科研与实践创新计划项目(SJCX21_0063)
国家重点研发计划项目(2018YFB1601001)
关键词
交通工程
租赁点规模
遗传算法
共享汽车
聚类算法
热点出行区域
traffic engineering
rental point scale
genetic algorithm
car sharing
clustering algorithm
hot travel area
