Study On The Logistics Park Location With Bi-level Distribution

With the constant development of China's economy, modern logistics plays a growing role in the economy. Logistics park is the development of modern logistics to a certain extent product and an important node in the entire logistics network. It plays a connecting link between the preceding and the following role in the logistics system. Logistics park location has great impact on the establishment of the logistics system. An appropriate and reasonable location can ensure the balanced development of the logistics system, improve the efficiency and quality of service of logistics park for the enterprise and customer, save logistics cost and promote regional logistics economic rapid development.This paper defines the basic concepts, important position, attributes, classifications and functions of the logistics park. Then it expatiates the general situation of domestic and international logistics park. At last, this paper analyses the principles and factors of logistics park location, the classifications of the location models, and the process and steps of the logistics park location. For the options unknown address of the logistics park location model, the paper uses iterative algorithm to solve the problem. It compiles the C++ program to achieve the algorithm, and uses examples to demonstrate the feasibility of the algorithm. For the options known address of the logistics park location model, the paper imports the factory in the model, and establishes a bi-level distribution of the logistics location model, which is a model of a direct distribution from the factory to the customer and a distribution from the factory by the logistics park to customer, considering the impact of various factors and the minimum total cost of the whole logistics operation, which is more in line with the actual logistics environment. In small-scale data, the paper uses Lingo10.0 to verify the accuracy of the building model. As the bi-level distribution logistics park location is a NP-hard problem, it is not easy to solve the problem when large-scale data using precision algorithm. The paper designs a two-step heuristic algorithm to solve the problem. In the first step, it uses the shortest path algorithm to determine the customers which are serviced by the factory and the initial logistics park distribution; in the second step, it uses simulated annealing algorithm to select by the initial distribution logistics park to optimize the customer to determine the final selection of the logistics park location and its distribution customers. At last, this paper achieves the algorithm by using C++ program. Through the calculation and comparison of the examples, it demonstrates the algorithm to solve the problem is feasible and effective.