OPTIMIZING DISTRIBUTION NETWORKS WITH NESTED GENETIC ALGORITHMS
O. BRUDARU 1, 2, B. VALMAR 2 1. Institute of Computer Science, Romanian Academy, IaĆi Subsidiary
2. âGh. Asachiâ Technical University IaĆi, Department of Management and Production Systems Engineering, Iasi, Romania, e-mail: brudaru@tuiasi.ro
This paper deals with the optimizing of distribution networks with a central depots and a prescribed number of intermediate depots that supply groups of clients. A two levels metaheuristic is described for solving it. On the first level, a genetic algorithm used for finding the feasible group of consumers and the corresponding intermediate depots, like in the p-median problem. For such a partitioning of the clients, the interior provisioning circuits are obtained by invoking a hybrid genetic algorithm, and this task represents the second level of the metaheuristic. This second level completes the partial solutions from the first level and computes the fitness function of the genetic algorithm on the first level. The performance of the metaheuristic containing the two nested genetic algorithms is experimentally evaluated.