Research On Supply Chain Management And Disposal Of Statistical Data

The globalization of economy make the whole world become a big uniform market since 90's 20 century.It begin to cross over national boundary for excellent allocating in resources fields,and for seeking the using efficiency and economy performance in limited resource makes it be true that the transform of logistics trend to a whole direction. As a result,the concept of supply chain management appeared.Therefore this have not only been one of important international theories in management science and engineering application,but also constructed a good suit point to solve actually problem between applied mathematics and reality requirement.Thus a great deal of researchers,include us,are attraced to the interesting work.As information ages arrive,the application study of supply chain management become more and more pay attention to the value of share information from every party of the chain.A kind criterion based on value chain is builded by the information data.It eauals the treasure hided in information resources for to discovery the value of information from the data.Generally speaking,it is real that the useful information containing value is usually hiding in sea quantity data.Only by guide line of statistics theories,we can carry out the data identify in detail,and get valid data processing based on science, so that we can withdraw the body value of the information data.In this paper,based on theorical knowledge background of probability statistics and stochastic process,and based on these theorical results ofδ-Shock model in reliability theory,we studied not only the structure problem of supply chain management,but also considered probability feature of the disposal technique of identifing abnormal data. These research results,which are divided into two part,not only based on the theoretical knowledge of probability statistics and stochastic process,but also on thinkful foundation ofδ-Shock model.On the one hand,we study the basic centralized newsvendor model with profit redistribution and decentralized newsvendor model with decision right re-distribution in supply chain management.It is diffrent from classical model that sale process is distinguished normal sale and promotion stages.Vendor can select to sales promotion for increasing their return when real demand is lacking.We get two mathematical expressions of traditional optimization order quantity Q~* and new optimization market size N~8.So,we extend the classical decision-making issue with one dimension to a new decision-making issue with two dimension.At the some time,we also yield the accurt mathesmatical expression formula of(Q~*,N~*) and discuss the effect of(Q~*,N~*) as some parameter change.On the other hand,we study the problem about identify and disposal of statistical data.In the process of reality investigation relatived to management for big enterprise,we find that the level of supply chain management is determined by data ability of pooling logistics run and fund run and information run together.Thus,we focus on considering data disposal with masking effect,we yield the joint distribution and limit distribution for many abnormal data,and follow the sample median test formula under exponential totality.In forecasting macroscopical economy with GDP,we propose a improving model of GM(1,1) while we also give structural modification for grey relation analyse.This dissertation consists of six chapters.A comprehensive survery about supply chain management is proposed in chapter one.In chapter two,we pay our attention to the basic newsvendor model with profit re-distribution,which is different from the classical newvendor model.Further,in chapter tree,we focus on and decentralized newsvendor model with decision right re-distribution in supply chain management as we do in last chapter.Next chapter,however,we major consider data disposal with masking effect by using AGO method,and yileld some results of union distribution and limit distribution under assume condition of H_k.A issue of statistics forecast to macroeconomy relative to GDP is arranged in chapter four.Under small.sample,some improvement ideas and methods of GM(1,1) are received.Chapter five is devoted to simulation investion.In the last chapter,the view point of prospect for the future work is provided while myself thinking experience is also given.The aim of the paper is to explore supply chain management and its application in practice by using stochastic processes methods,and while study the identification and disposal of statistical data with special value.Our result in the paper is important and meaning in theory and practicality.