Based On Fahp And Bp Neural Network Research, The Issue Of Third Party Logistics Distribution Center Location

In recent years, with the rapid development of socio-economic and science and technology; with shrinking of first and second profit source; with the pace of economic globalization accelerated. Logistics is becoming increasingly important; more and more people pay attention to it. Therefore, how to tap the potential of logistics, improve social results and save resources is a new strategy of the enterprise.With the third-party logistics in the national economy becomes more and more prominent, as a logistics network node in the third-party logistics distribution center is increasingly important. The location of third party logistics distribution center plays an important strategic position in the planning and designing of distribution center site. To some extent, the location of distribution center advantages or disadvantages, which will decide the third-party logistics distribution centers is successful or failure.At present, the decisive methods of logistics center location exist two problems: first of all, the affect of the location factors are very much. We often only consider the money of construction and the transporting the location, many unquantifiable factors are not considered. Secondly, when there are multiple candidate points or more location layers. Many people don't establish a rational evaluation system. They often choose the candidate with experience. So it is lack of scientific. Therefore, the traditional location models must meet some of the applicable conditions, so there are some limitations. In this paper, using the fuzzy comprehensive evaluation method to assess, at the same time, using analytic hierarchy process( AHP )method to determine the weight of each factor. getting the training samples that it is used for distribution center location of BP neural network.In short, the location of logistics distribution center occupies a very important position in the whole logistics system. Policy-maker must consider many factors. However, in the traditional algorithm, some important qualitative factors are ignored. Using BP artificial neural network to process data, which can avoid the lack of traditional algorithm. Using examples illustrate the process of the method.