GA applied method for interactively optimizing a large-scale distribution network

Based on experimental comparison, this paper discusses approximate solution methods of the medium-scale traveling salesman problem (TSP) that suit repetitive use in interactive simulation for globally optimizing a large-scale distribution network. For example, such a nationwide distribution network consists of approximate 1000 trucks. So, the optimization of such a distribution network needs repetitive interactive simulations, in each of which about 1000 TSPs are automatically solved after changing such conditions as the area division and the truck allocation and a human user waits and checks the results totally. Therefore, our proposed method applied genetic algorithms (GA), guarantees interactive responsiveness and realizes experts´ level accuracy, through enabling to solve 1000 middle scale TSPs for a distribution network within 30 seconds within 3% errors. Experimental results proved that the proposed method enables to optimize a large-scale distribution network