Integrated demand forecasting and capacity control for segment-based airline revenue management

Censored demand data reduce forecast accuracy, and the common separation of forecasting from optimization often leads to suboptimal seat allocations and diminished revenue in airline revenue management. This study proposes an integrated framework that jointly addresses demand unconstraining, forecasting, and capacity control, with performance assessed through simulation. Using historical data from a major Chinese airline, we evaluate Expectation–Maximization (EM) and Projection Detruncation (PD) unconstraining methods combined with Expected Marginal Seat Revenue (EMSR) heuristics. Our results underscore the critical importance of demand unconstraining, with PD outperforming EM. Compared to the airline’s experience-driven approach, the integrated framework delivers substantial improvements in both revenue and decision quality. Notably, even a simple, tractable optimization model, when paired with properly unconstrained and updated forecasts, captures most of the benefits of full integration.