The Decision-making Of Long-term Location Of Logistics Crunodes Project

Logistic crunodes are the key parts of logistic network. The location of logistic crunodes project becomes the most important strategic problem in the development of logistics, which will directly impact the realization of function and benefit. In a word, the location is very important in the process of logistic network programming. The location problem of logistic crunodes project is widely researched. There are many researches to resolve this problem from the quality and the quantity. However, those researches were mostly based on minimizing the total cost during the building up or minimizing the transport routes, rarely considered the running cost after handing over the logistic crunodes project. The long-term location mentioned in this article, not only considers the cost during building up, but also considers the running cost after handing over, then basing on minimizing total cost, sets up models for decision-making,This article sets up mathematic models form from static and dynamic aspects, according to the different characters of different logistics crunodes. And the long term condition is considered in the models in this article. Firstly, we use the Analytic Hierarchy Process (AHP) to filter primarily, and then use the discount method to make the long-term cost in current value. About these logistic crunodes projects which will not change the location, once been decided, based on0-1integer programming models, this article sets up a long-term static programming model. While about these logistic crunodes projects which may change the location in different time, based on dynamic programming models, this article sets up a long-term dynamic programming models. For long-term static model, the method of exhaustion is used to resolve it. Considering the changeability of long-term location, we use the method of dynamic programming to resolve the dynamic model. This article sets up different mathematic models for different logistics crunodes project. It makes the models more realistic, and improves the accuracy of the decision-making for the location.