Research On The Planning Of Urban Online Shopping Logistics System By The Use Of Four-stage Method

With the rapid development of information technologies including Internet,cloud computing,big data,Internet of things(IoT),new economy has recently gained great progress in modern society,which brings a large number of profound changes in people's living behavior and consumption custom.As a result,this has resulted in overall advancement in online shopping logistics industry.At the same time,it also leads to many municipal and transportation problems.Therefore,it is still desirable to develop a series of effective theories and methodologies to deal with various issues in planning and management of urban online shopping logistics systems,so as to provide an important scientific basis and theoretical support in decision-making and management departments for the municipal governments.It has been noticed that many existing studies on urban online shopping logistics are only confined to some specific problems,and many of previous researches on traditional logistics cannot currently characterize the practical nature of online shopping logistics.To do so,after summarizing the definition,procedure and structure of urban online shopping logistics,this thesis is devoted to developing a systematic framework of analytical procedure for demand forecasting,demand distribution,number and scale of nodes,and node location and planning based on the classical traffic four-stage method.The main contents of this thesis are summarized as follow:Firstly,a linear regression prediction method and ARIMA time series prediction method with respect to the characteristics of online shopping logistics are proposed respectively.The prediction indexes and influencing factors of linear regression method are introduced,and the smoothing process and parameter calibration of ARIMA model are then presented.Furthermore,Shanghai is taken as an example to illustrate the feasibility and effectiveness of two kinds of prediction schemes.Secondly,the relationship and influence factors between the overall scale and spatial distribution of logistics nodes are investigated,and the classification of online shopping logistics demand are then made.The transit logistics demand distribution is analyzed by using the means of AHP,and the delivery logistics demand distribution are then given.Moreover,Shanghai Xuhui District and relevant streets are used as the examples to present the distribution of logistics demand.Next,the characteristics of node scale and number in the logistics system is discussed.A design scheme of terminal node number corresponding to the regional logistics scale is put forward by combining with the means of quantitative calculation and qualitative analysis,and thereby making a scheme of the terminal node configuration for Tianping Street with four communities in Shanghai City.Finally,the upper node location problem is determined by the use of AHP method,and a bi-level programming model with the highest service level and lowest operating costs of the terminal node is formulated,and the genetic algorithm is employed to solve the model.To this end,TransCAD software is given to analyze the process of planning problem for the terminal delivery route.