Using Genetic Algorithms to Solve Large-scale Airline Network Planning Problems

AbstractThe airline planning process, including network planning and fleet assignments, is a complex and highly integrated strategic process involving multiple interrelated sub-problems that must be solved simultaneously. For example, analysing the e_ect of new technologies or changes in passenger demand or airline structures from an operational perspective requires the analysis and application of complex, structured airline planning resulting in extensive and complicated optimization problems. In this paper, we present an assessable formulation and approach to integrate network planning and scheduling as well as minor e_ects of aircraft rotation and passenger demand, which are solved by applying genetic algorithms. The objective function comprising direct operating costs, including costs of ownership and revenue, is based on heuristics that enhance the understanding of the airline's final profit composition