Optimizing The Location Of Virtual Stations In Free-floating Bike-sharing Systems With The User Demand During Morning And Evening Rush Hours

In recent years,with the development of technologies such as the Internet of Things,mobile payments,and smart phones,the shared bike has emerged and has been widely used.the shared bike has played a greater role in solving the "last mile" problem,urban congestion and environmental pollution.Compared with the public bicycle system,the free-floating bike-sharing system has the advantages of low cost and convenient use.However,some problems also occurred during the development of the free-floating bike-sharing system,the most prominent of which is the location of virtual stations.Specifically,the phenomenon that distribution disorder of virtual stations in the free-floating bike-sharing system has made it difficult for users to find a shared bike and use it.This phenomenon is serious in the morning and evening rush hours.Therefore,the purpose of this study is to optimize the location assignment of virtual stations that can meet the growing demand of users by analyzing the usage data of their shared bikes.While increasing the use of bike-sharing rate and operator revenue.This study combines the user demand analysis and facility location selection to optimize the location of virtual stations in free-floating bike-sharing system.Firstly,the literature of the shared bike' is sorted and summarized,and the research status of the location of virtual stations in free-floating bike-sharing system is clarified.The related theories of shared bike and user demand are summarized,and the operation mode of shared bike is understood.From the two dimensions of time and space,the user demand is analyzed to determine the specific characteristics of user demand.According to the characteristics of user demand,it is defined and quantified,and integrated with the facility location model.This paper investigates a virtual station location problem in free-floating bike-sharing system,and a mixed-integer programming model is proposed to maximize the user demand.Based on problem nature and characteristics of model,a clustering algorithm is designed to solve our problem.Finally,a case study of the usage data of Beijing users from the 2017 Mobike Algorithm Competition was conducted.The results show that the location model and the clustering algorithm can effectively optimize the distribution of virtual station in the free-floating bike-sharing system,meet the needs of operators for the planning of free-floating bike-sharing systems and further prove the rationality and effectiveness of the model and algorithm.In summary,the location model and the clustering algorithm is proposed in this paper,which can not only provide new ideas for the optimization of hub location research but also provide a theory for operators to plan a free-floating bike-sharing system.In the end,it can also provide decision support to government agencies in optimizing urban traffic layout.