Unleashing the potential of operations research in air transport: A review of applications, methods, and challenges

Abstract

Operations research (OR) has been applied in air transportation since the post-war period, starting from relatively simple static models and classical linear optimization techniques. Recent advancements in operations research, computational intelligence, and data management have significantly transformed the landscape of OR applications, addressing the growing complexity and demands of the modern aviation industry. This study explores the latest developments of OR applications within air transportation, focusing on key areas such as airline management, airport management, and air traffic management. We delve into the integration of big data, artificial intelligence and sustainability aspects, which has enabled unprecedented precision in, e.g., flight scheduling, air traffic control, and predictive maintenance. The adoption of modern heuristics based on machine learning algorithms and advanced solution techniques has facilitated to solve an increasingly larger and more complex set of mathematical models for improved resource allocation. This paper also highlights the shift towards holistic and integrated OR models that encompass the entire air transportation ecosystem, from airline operations to airport management. By analyzing these recent developments, we underscore the critical role of OR in driving efficiency, safety, and sustainability in air transportation, offering insights into future trends and potential research directions in this rapidly evolving field.