| Logistics management not only be considered as the core of cost, profit and service, but also be seen as the core of long-term development strategy. The location of logistics network node is logistics strategic decision, it has a pivotal role both for the entire country's logistics industry, or the enterprise's logistics network planning and efficiency, etc.Based on the rapid development of urbanization in China like the number of cities increasing and the expansion and extension of urban. This thesis attempt to introduce the geographical cellular automata to simulation and prediction urban expansion and changes, to solve the problem of prediction uncertainty, then provide more practical theory for the dynamic location. We established a dynamic logistics network node location model based on a CA simulation to estimate changes in demand for urban development, which is logistics network node dynamic location based on urban development, the model get a better solution to the dynamic logistics network node location demand estimates uncertainty problem, combined with dynamic programming techniques to simulate the solution process, it making the dynamic location model more realistic.Use dynamic programming techniques to solve the location model, the simulation results show that, the total six periods dynamic location costs saving about 345.4krmb than static location. Not only simulation of urban development and the change in demand(with CA), but also reflects the trends in the logistics better, and find a dynamic location decision based on the economic and social environment, showing a clear economic benefits.By change zoning, neighborhood setting, rule-making of CA, and change the dynamic location model, our model can be widely applied to require long-term planning, and demand is difficult to determine location problems. Using a similar model can not only solve the problem of logistics network node location, but also provide advice to the location of urban facilities. |
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