Evolutionary Computation for Air Transportation: A Survey

As the demand for air transportation continues to grow, airspace congestion, flight delays, operational costs, and safety have become important and challenging issues. There are various optimization problems in air transportation, which involve large-scale data, complex operational scenes, multiple optimization objectives, and dynamic environments. In addition, besides conventional commercial aviation, the development of urban air mobility brings new features to air transportation. Evolutionary computation (EC) algorithms have emerged as a promising approach for solving optimization problems in air transportation. This article introduces a hierarchical taxonomy to systematically review the application of EC algorithms in air transportation. At the first level, related studies are categorized into commercial aviation and urban air mobility based on their application domains. At the second level, studies are further classified according to different operational scenes. A comprehensive review of relevant studies in the literature is presented according to the above taxonomy. In addition, future research directions and open issues are discussed to support and inspire further advancements in this field.