An Efficient Genetic Algorithm for the Design of Hub-and-Spoke Networks

We propose an efficient genetic algorithm (GA) for the design of hub-and-spoke networks with single allocation. The creation of the initial population is based on the greedy randomized search procedure, which provides high quality individuals. Furthermore, new crossover and mutation operators were implemented in order to improve the solution over the evolutionary process. Additionally, a local search procedure is applied in the best individuals. The adapted GA is tested in the Australian Post (AP) and Civil Aeronautics Board (CAB) data sets and clearly outperforms four other evolutionary algorithms of the literature, both in solution quality and CPU time.