A Genetic Algorithm Based on Complex Networks Theory for the Management of Airline Route Networks

Abstract

Airline companies need to organize and manage their route networks in a more cost-efficient and reliable way, in order to cope with increasing customer demands and market changes. This paper attempts to apply complex network concepts and techniques to model airline route networks, and the focus is then put on how to develop an effective and efficient Genetic Algorithm (GA) to optimize airline route networks in terms of certain network properties which are identified to have crucial roles to play in making airline route networks cost-efficient and reliable. The chromosome structure in the proposed GA is based on complex network modelling, and as a result, effective evolutionary operators, particularly a highly efficient uniform crossover operator, are developed. The results demonstrate that the reported GA has a good potential to improve the topology of airline route networks in terms of network properties of interest such as operating costs and network robustness.