Application of Complex Network Theory and Genetic Algorithm in Airline Route Networks

Abstract

To cope with increasing customer demand and market changes, airline companies need to organize and manage their route networks in a more cost-efficient way. In addition, the robustness of flight operations against unpredictable accidents such as terrorist attacks and natural disasters has become more important to airlines. In this study, the concepts and techniques from complex network theory are used to model airline route networks, and then an effective and efficient genetic algorithm is developed to optimize airline route networks in terms of network properties that may have crucial roles to play in improving the cost-effectiveness and reliability of airspace systems. The simulation results illustrate that the work reported in this study has a good potential to improve the topology of airline route networks in terms of given network properties such as operating costs and network robustness.