Research On Static Redistribution Of Urban Public Bicycle

With the rapid development of China's economic growth and urbanization,how to develop the public transportation system has become a top priority,under the slogan of “sustainable transportation”,the development of urban public bicycle also play an increasingly important role.As a popular choice for the public,public bicycle can solve the problem like urban congestion,environmental pollution,waste of resources and so on.While we enjoy the convenience of public bicycles,public bicycles also involve a series of problems such as management,operation,distribution and optimization,and the scheduling problem of bicycles has always been the key research issue of the urban public bicycle system.How to achieve a better "pick-up or drop-off " demand is the main content of this paper.Based on the stock data of public bicycle stations,this paper will redistribute each station through modeling and algorithm operation to achieve better redistribution results.The main research contents are as follows:(1)Estimate the initial optimal stock levels for each station based on historical data of public bicycle station.First,introduce and estimate the penalty function of each station as a function of the initial inventory level,followed by calculating the total penalty value of the entire public bicycle system to minimize the stock level of each station,and finally establish a nonlinear program to ensure the invariance of the total number of bicycles in the public bicycle system before and after redistributioning.(2)Based on the above calculation results,complete the study of static redistribution of public bicycles,focusing on the estimation of the optimal inventory level of public bicycles after static redistribution operations,and introducing the problem of static redistribution of bicycle problem(SBRP),two static redistribution models(ResSBRM and RelSBRM)have been introduced.Under the condition of restrict model,the partial path problem is solved by constructing a mixed integer linear program(MILP),under the condition of relaxed model,the factor of the penalty value is introduced to ensure that the loading vehicle completes the static redistribution in each public station with desired inventory level.(3)Considering the limitations of the RelSBRM and ResSBRM models,it is more suitable for small network parts,and a heuristic algorithm is developed to estimate the optimal solution of large networks.The heuristic algorithm assigns weights to the network edge of the public bicycle,and the weight matrix can form a set in the public bicycle network.The set is processed and optimized according to the principle of demand first.The results obtained by the heuristic algorithm are compared with the results of the MILP model.It is found that the heuristic algorithm is beneficial to solve the static redistribution problem in the large public bicycle network..This paper focuses on the static redistribution problem of urban public bicycles(SBRP).Through various parts of research,it will better serve the public bicycle system,it scientifically and rationally promotes the problem of "pick-up or drop-off " demand",it has contributed to the development of public transport too.