Application Research of Genetic Algorithm in Automobile Logistics

In recent years, with the increasing trend of the cost of production and management, the decreasing of the profits, as well as effects of some external factors, China's automobile manufacturing is facing unprecedented challenges. How to reduce the cost of production in the premise of guaranteeing their quality becomes a key for the survival and development of the enterprises. At present, China's automobile logistics cost accounts for more than 20% of the production of motor vehicles. Therefore, lowering logistics cost by seeking its best path is an effective way to lower the cost of automobile manufacturing. This paper combines the Graph Theory and the genetic algorithm to research the optimizing problem of the lines of logistics distribution. Traffic flow data under normal conditions is obtained through field studies, based on which we can calculate the time of the network weight through appropriate method, find the best lines of distribution through the optimization theory of genetic algorithm, and show the feasibility and superiority of the method through examples.