This paper regards the four location problems, such as distributing center, warehouse, fetching cargoes and cargoes distributing routing, as an abstract problem. This four location problems are widely applied in traffic, transportation, storage, industry explore and etc. In recent years, location problems in logistics are a hot topic in the world. Based on the classification of four location problems, this paper mainly draws out distributing center models of location problems from the theory, analyses and implements its proper optimal algorithm. Because distributing center location places an important part among the logistic location problem. Its reasonability will greatly reduce enterprise's costs, including transport cost, building cost and some variation cost. Obviously the research is significant. The specific contents as followings:Firstly, this paper gives out location problem. The location problem is about selecting the optimal locations for the building facilities. And drawing them out location problems will solve the problems in logistic system. Mainly some influence factors to distributing center location are analyzed and some usual location methods are researched.Secondly, a comprehensive and universal function model is provided based on above abstract. In many modeling methods, only AHP has both quantity analysis and qualitative analysis. Considering the complexes of logistic system and the diverse of influence factors, this paper chooses AHP to hypothesis, model and check in logistic location problem. Meanwhile it also introduces AHP's idea in detail.Finally, resulting in the characters of the logistic system and the model, two valid optimal algorithms are selected. They are stimulating annealing algorithm and genetic algorithm. By analyzing and comparing their ideas, one table is listed with the factors, such as the property of results, initial values, restrict conditions and the speed of convergence. Considering some deficiencyof GA when solving such problems, a new algorithm-stimulating annealing merged with GA is put forward. And I implement the location model with genetic algorithm and stimulation annealing merged with GA. Then I give out some experiment data and the ideas of the algorithms.After some study and with the former theory analysis, the expected result is acquired. It greatly simplifies the location problem of logistic system. This verified its applicability in this field. At the same time the stimulating annealing merged with GA optimal algorithms is used better. |