共享单车需求预测及调度优化  

Demand Forecast and Scheduling Optimization of Shared Bicycles

作　　者：刘恒孜 贺玉龙[1] 宋太龙 许鹏 LIU Heng-zi;HE Yu-long;SONG Tai-long;XU Peng(Beijing Key Laboratory of Traffic Engineering,Beijing University of Technology,Beijing 100124,China)

机构地区：[1]北京工业大学,北京市交通工程重点实验室,北京100124

出　　处：《科学技术与工程》2021年第35期15247-15254,共8页Science Technology and Engineering

基　　金：国家重点研发计划(2017YFC0803903)。

摘　　要：为了更加准确地预测共享单车的需求量,制定合理的调度优化方案。针对共享单车骑行数据的周期性、非线性和随机性的特点,提出了季节性灰色Markov模型来预测共享单车需求量。在此基础上,根据双层规划模型结果来制定调度优化方案。在季节性灰色Markov模型中,首先将原始数据代入季节性GM(1,1)模型得到预测结果,然后用Markov模型对预测的残差进行修正,得到最终的预测值。在双层规划模型中,上层目标为运营商的调度成本,下层目标为调度中心的调度时间,双层规划模型用GUROBI求解器求解。最后将两种模型应用于纽约市17个Citi Bike共享单车站点的算例分析。数值计算结果表明:季节性灰色Markov模型在17个站点从周一到周五的需求量预测的平均绝对百分比误差(mean absolute percentage error,MAPE)为10.68%,预测精度较高。利用双层规划模型制定的调度优化方案能确定调度中心数量、位置,调度范围和调度路径,可以在满足用户需求的同时使调度成本和调度时间最优。研究提出的需求预测模型和调度优化方案可以为共享单车运营部门和交通管理部门提供有效的参考。In order to more accurately predict the demand for shared bicycles,a reasonable scheduling optimization plan was formulated.In view of the periodicity,nonlinearity and randomness of the shared bicycle riding data,the seasonal grey Markov model was proposed to predict the demand for shared bicycles.On this basis,the scheduling optimization plan was formulated according to the results of the bilevel programming model.In the seasonal grey Markov model,the original data was firstly brought into the seasonal GM(1,1)model to obtain the prediction results,and then the Markov model was used to correct the predicted residuals to obtain the final predicted value.In the bilevel programming model,the upper layer target was the dispatch cost of the operator,and the lower layer target was the dispatch time of the dispatch center.The bilevel programming model was solved by the GUROBI solver.Finally,the two models were applied to the analysis of 17 Citi Bike shared bike stations in New York City.The numerical results show that the mean absolute percentage error(MAPE)of the demand forecast from Monday to Friday for the seasonal grey Markov model at 17 sites is 10.68%,which means that the forecast accuracy is relatively high.The scheduling optimization plan based on the bilevel programming model can determine the number,location,scheduling range and scheduling path of the scheduling center,which can optimize the scheduling cost and scheduling time while meeting user needs.The demand forecasting model and scheduling optimization program proposed by the research can provide effective reference for shared bicycle operation departments and traffic management departments.

关 键 词：共享单车 需求预测 季节性GM(1 1)模型 MARKOV模型 双层规划模型 调度优化 

分 类 号：U484[交通运输工程—载运工具运用工程]