Research On The Model Of City Joint Distribution Center Location

Urbanization process and increasingly prominent of urban problems, require enterprises to improve distribution efficiency and service delivery level, we must also pay attention to the ecological environment protection. However, the pursuit of the traditional distribution center location is to maximize the economic benefits, ignoring the impact on the environment, so that lead to inefficient distribution of resources, energy waste and ecological damage to the environment, all do not meet the ecological civilization and sustainable development requirements.Meanwhile,the construction of distribution centers needs a large number of infrastructure, such as stationary machinery and plant, and spend more time and money, making it difficult to move once completed, if inappropriate siting, will heavy losses. Thus, during the construction of city joint distribution system, location problem is a vital part. Its advantage is not only able to complete the entire logistics channels, so that distribution can be optimized, while improving the economic efficiency of enterprises, enhance low-carbon logistics environment competitive advantage, but also reflects the logistics system resource optimization concept, and ultimately business "zero inventory" goal.In this paper, niche fitness measure and mixed integer programming method are combined, the ecological suitability factors of qualitative advantages and mixed integer program method of quantitative organic fusion, which is a more applicable approach to decision making. First of all, Learn from their predecessors have been summed siting factors, screening ecological suitability factors affecting the siting and scored,and entropy method determined by the weight of each factor’s weight, to calculate the relative value; then, On the basis of the original distribution center location model, taking into account the recovery of logistics costs,using mixed integer programming method to determine the decision variables affect the siting of the cost factor that is limiting the integer part of the variable value, and then determine the constraints and objective function; and finally, the use of Matlab software simulation analysis to achieve optimal site selection program.