Robust Optimization of Hub-and-Spoke Airline Network Design Based on Multi-Objective Genetic Algorithm

Abstract

In the process of designing hub network, the selection of hub airports is influenced by the change of the demand and cost. Under the condition of changing in demand, this may lead to large minimum cost deviation between the designed optimal network and real optimal network, respectively. To reduce the risk caused by the uncertainty in network optimization and get the optimal robust solution of hub network under the multi-possible conditions of demand and cost, a method based on multi-objective optimization genetic algorithm is proposed in this paper. The convergence of the algorithm has been proved, and the experimental results demonstrate the availability of the algorithm. First, multiple objective functions needing to be optimized simultaneously are formulated from different conditions of needs and cost, then a genetic algorithm is used to provide all possible routes of the network hub structure, and robust optimal network solution for multi-objective optimization is searched. The convergence of the search algorithms is proved to be effective by the numerical results.