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Research And Empirical Analysis On Automobile Logistics Demand Forecasting Method

Posted on:2017-01-08Degree:MasterType:Thesis
Country:ChinaCandidate:J YangFull Text:PDF
GTID:2492306737995609Subject:Logistics Engineering
Abstract/Summary:PDF Full Text Request
This paper systematically reviews the main methods of the domestic and overseas logistics demand forecasting,and lays a foundation for revealing the characteristics of automobile logistics demand by analyzing the production mode,production order mode,automobile supporting relationship mode,parts logistics mode and vehicle logistics mode of automobile industry.Secondly,auto logistics demand is divided into parts and whole vehicle logistics demand.Based on the whole vehicle output as the benchmark quantity,the forecasting method of whole vehicle output is proposed.Based on this,the forecasting method of parts logistics demand and whole vehicle logistics demand is constructed.Thirdly,by the open area with Chengdu auto industry as the empirical object,for the district of automobile industry development present situation and planning condition,and the analysis of automobile logistics mode and the internal structure,based on the production and transportation coefficient,conversion ratio and other methods,the technical route of logistics prediction is established,which can predict the model of vehicle output,vehicle logistics demand and parts logistics demand to analyze the influence of predicted value on traffic network.Finally,from the perspective of logistics model innovation,logistics resources optimization allocation and key project overall arrangement,the thesis provides policy Suggestions for the development of automobile logistics in the development zone.The research results of this paper are helpful to deepen the application of logistics demand forecasting in automobile industry,which can provide decision-making reference for optimal allocation of logistics resources and formulation of logistics planning scheme in Chengdu economic development zone.
Keywords/Search Tags:Automobile logistics, Demand forecasting, Traffic impact, Prediction method
PDF Full Text Request
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