| With the rapid development of Information Science in recent years, modem logistics has entered a stage of rapid development of information and intelligence. In particular geographic information system in theory and application for the rapid development of modern distribution problem laid the foundation.Genetic algorithm is based on a genetic hybrid, natural selection and mutation search algorithm. It has a random,highly parallel and overall advantages. Because of its simple structure and strong robustness, can be a very good solution to the traditional search algorithms to solve the nonlinear function optimization problem, so it is widely used. Effect of genetic algorithm performance factor is very much, which is important for comparison with and mutation operation related parameters. If these parameters are not good enough, the genetic algorithm is easy to premature convergence.This paper studies the principle of genetic algorithm, analyzes the parameter influences on genetic evolution, and in the light of the shortcomings of simple genetic algorithm, fuzzy theory and genetic algorithm combines, put forward a kind of fuzzy genetic algorithm. This issue through the design of a fuzzy controller, according to the evolution processes of various real-time of crossover probability and mutation probability were adjusted, thereby accelerating the algorithm running speed, avoid premature convergence.Logistics system optimization for logistics distribution center location is a very important problem. Through the analysis and research of traditional logistics distribution center location based on the insufficiency, this article establishes a based on GIS and genetic algorithm logistics distribution center location model. The model first determines the distribution center site selection requirements and may influence the location of each factor, and then uses the GIS platform to obtain a series of candidate locations and the use of genetic algorithm to solve the optimal locations. |
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