The application analysis of genetic algorithm in integrated reverse logistics supply chain network designAuthor(s): Peipei Diao
According to clients' needs and the limit of existing infrastructure skillï¼the total cost to the principle of minimum, insure both of forward logistics and reverse logistics. Fix the topological structure and then do the supply chain network design. People can use Priority coding genetic algorithm to get optimal solution of the supply chain network designing model. According to the basic principles of genetic algorithmsï¼dividing the process of supply chain logistics activities into four partsï¼use not niced coding method to code the four parts. The purpose is to make this algorithm fast and accurate. When we determine the initial population can use Greedy heuristic algorithmï¼then do genetic manipulation to make it produce offspring and insure both of the cross operator and mutation operator at the same time. After designing the model and algorithm, make one area's Supply chain network design for example to test the correctness of the model and algorithm. The design process clear that the total number ï¼ location and feature of the factory and railway freight station which are need to be established. And in terms of calculation time we also compared with other algorithms. The results show that this genetic algorithm can obtain the optimal supply chain network design solution and use the shortest time.