Improved Genetic Algorithm And Its Application On Location Of Logistics Distribution Center

Logistics distribution center has play an important role in modern commodity society, it seeks to identify and achieve lowest cost, improve inventory cycle time and performance cycle of product, etc by integrative process management of delivery, warehouse, loading, procurement, customer order and information order. Recently, the research of delivery center has become as a hot topic, however how to choose location of delivery center is a very significant question that we have to consider today.Genetic Algorithms is based on Biological evolution theory, the main feature is group search strategy and the individual of the group can translate information. It is developed by Professor Holland who graduated from Michigan University. In recent few years, it has used in solving complex optimization problems and industrial areas.This paper first introduces the current situation about the study of Genetic Algorithms and location problem. It has combined the real problem in the site selection and the method of how to solve it. Then introduce the Genetic Algorithms theory and the areas it to be used and some drawbacks of this theory. In addition, it also mentioned how to improve this theory.Now mostly researches about site selection model are concentrating on self construction, this is not coincident with the real situation. Because the mostly possible choice is outsourcing, that is to say give their distribution center's management to the third party. Even this center is contributed by themselves, the lower distribution is also charge by the third part, so the present papers about location problem have lack the instructionFrom the point of actual problem in site selection, this paper put forward a bi-level programming model based on third part logistics. On base of balancing the behalf of self management distribution central and Outsourcing distribution central, we construct the constraint condition. The improved Genetic Algorithms is used to solve the model. Compared with traditional methods, it works fast and easy to generalize.Finally, we set one enterprise as an example, and according the actual condition to set up model, then apply the Genetic algorithm's coding technology, so that we can realize the iterative calculation. Contrast the tradition methods, we will found the superiority of Genetic algorithm.