Air Cargo Operations Research: Current Limitations and Future Directions

Air cargo operations research (OR) involves the development and use of applied mathematical techniques to optimize a variety of outcomes such as on-time performance, financial metrics, or environmental impact. Due to the complex, dynamic, and commercially sensitive nature of real-world air cargo operations, such studies must strike a practical balance between realism, generality, and tractability subject to available data. In this literature review, we critically analyze and synthesize findings from peer-reviewed research papers published between 2015 and 2025. A total of 152 papers were reviewed using PRISMA guidelines, with an emphasis on comparing research methods and goals. Mixed-integer linear programming remains popular, supplemented by emerging heuristics and dynamic programming techniques. Demand is typically captured by gravity models fitted to socioeconomic variables, with emerging attempts to include the impact of intermodal choice. The complexity and rigour of cost functions have expanded to include variables beyond time and money. In addition to the classical goal of maximizing financial returns, recent studies increasingly aim to improve network resilience in the face of disruptions, accommodate growth due to e-commerce, assess environmental impact, and improve the computational efficiency of OR techniques.