Research On The Operation And Scheduling Of Urban Public Bicycle

With the increasing popularity of the concept of Green Travel,public bicycle transportation has been greatly promoted worldwide.Public bicycle transportation is convenient for short and middle distance travel and easing traffic congestion,in the meantime,it can connect with subway and bus,expand the service area of public transportation effectively,as well as improve the service quality of public transportation.However,the lack of scientific operational and managing methods causes the problem of “hard to borrow,hard to return” to stick out in the daily operation of public bicycle,which severely affects the user experiences of the travelers and restricts the further development of public bicycle.Under the above circumstance,researches about the operation and scheduling of urban public bicycle system is of great significance to the logical and effective scheduling of public bicycle resources,and improvement of the service quality.The paper studies several major aspects of public bicycle system management,including region division,scheduling demand forecast,customer satisfaction quantization,and vehicle scheduling routing optimization,etc.The major research work are as following:First,analyze the travel characteristics of public bicycle system based on actual operational data,and then proposes regional management as well as the region division method based on P-median model.In the meantime,the paper develops relative calculational steps to obtain region division results and determine the scheduling center of each joint operational region.It is proved by case study that the method is convenient to apply,works well with the space radiation characteristic of “short distance travel” of public bicycle,and is feasible in practice.Second,propose different scheduling demand forecast methods for night and peak periods demands.For the peak periods scheduling demand forecast,the paper applies weighted moving average method,develops the forecast model combining historical data and reservation data,and conducts case analysis to the model based on actual operational data,which lays the statistical basis for the following scheduling optimization work.Then,make quantization to customer satisfaction based on parameters such as borrowing rate and returning rate.In the meantime,the paper develops the peak periods scheduling model based on minimum total cost night scheduling model and minimum total cost and maximum customer satisfaction peak periods scheduling model,and applies genetic algorithm to solve the model.The case analysis shows that,through comparison with the current method,the optimized scheduling method advances in all aspects such as constant cost,travel cost,and customer satisfaction.Finally,after analyzing the differences between the shared bicycle and the pile type public bicycle,determine the future development trend of public bicycle,and then explore the similarities and differences between the shared bicycle scheduling and the pile type public bicycle scheduling.Finally,with the help of SWOT matrix,the paper proposes development strategy,and provides implemental suggestions.