Study On Modeling And Algorithm Of Distribution Centers Location Problem

In recent years, with the rapid development of the social economy and the economical globalization step speed up gradually, logistics become more and more important in the social economy development, and the people pay widespread attention to it gradually, so that the comprehensive level of logistics of a country become a standard by which judge its comprehensive national strength. The importance of logistics in the national economy is remarkable day by day, and distribution center as the node relate upstream and downstream of the logistics network, which also is paid attention gradually by the people. Distribution centers location decided the structure and the scale of the entire logistics network, affect the logistics expense in the system and the service level to the customers. Regardless of the entire national logistics industry development, or an enterprise's logistics network planning, distribution centers location decision-making has the pivotal function.In this paper, firstly in view of the planar location problem, a kind of particle swarm optimization (PSO) algorithm with chaos is constructed by adding chaos to influence the update of the velocities of particles. The technique can either avoid that the population trap into the local optimum or accelerate the convergence rate. Thus enhance the ability to seek the optimum and the evolution velocity. Next, in view of the discrete location problem, an uncapacitated distribute centers location model was established. Since the solution obtained by the neighborhood search is strongly dependent on the initial solution, the genetic algorithms with multiplicity individuals, and the strong ability to search the global optimum. We proposed a kind of hybrid genetic algorithms which is constructed by adding the neighborhood search thought to the genetic algorithms, and then applied it to solute the uncapacitated distribution centers location model. Moreover, the parameters of hybrid genetic algorithms were researched in the process. Finally, according to the thought of green logistics, considering both logistics costs and the gas emissions, we established a weighting model.