Location Model Of Logistics Distribution Center Under Uncertain Environment

Location problem is a class of significant real issue, the challenge of where to select the best site facilities has inspired a rich, colorful and ever growing of literature. Into21th century, especially in recent years, logistics industry plays an important role in promote the development of economic. Logistics distribution center is a modern logistic facility which engaged in allocating goods, delivering goods and the high standard service of marketing and supplying. It is like a bridge which links enterprises and customers. It is important for logistics managers to select suitable distribution centers. A good distribution center location can greatly boost the effect of transportation, and lower the operating cost of enterprise, and bring conveniences to our life. On the contrary, bad sites could lead to enormous loss, even last for a long time.Summarizing the history of the study, models were established under the deterministic envi-ronment in the early years, and then some scholars consider stochastic programming to establish a probability model based on probability theory. As many scholars had said that the establishment of probabilistic model requires a large amount of historical data, so as to obtain the distribution function of random variables in the model. But when there is insufficient historical data or data invalid, then probabilistic model lost its meanings. To deal with this problem, Professor Liu pro-posed the uncertainty theory. Theory and practice has proved that uncertain theory is an effective treatment tool to deal with nondeterminacy. This paper is based on this theory, and build uncertain programming model to accomplish the decision goals.The outline of this paper as follows. In chapter1, we first introduce the current situation and research status of logistics distribution center location problem, and then state the idea of establish uncertain programming model:regard the demand of customers and established cost of distribution centers as uncertain variables, then two kinds of model are established to determine the selection of the distribution center by solving the model. The second chapter introduce some basic concepts and properties about uncertainty theory associated with this paper. The third chapter first describes the basic flow of logistics system, after that, we discuss how to choose the best location from the candidate sites; then describe how to get the distribution of uncertain variables; then establish the expected value programming model; the last section gives an example to illustrate the actual meaning of the model. The fourth chapter focused on different modeling ideas and provide the uncertain chance-constrained model, and then give an example. Finally, the conclusions and forecasts are given.