Abstract This paper presents a comprehensive modeling framework aimed at addressing the capacity allocation problem for the upcoming schedule planning period within the context of large-scale airlines. The primary objective of the framework is to establish optimal flight capacity allocation per fleet type, with the ultimate goal of maximizing the overall profitability of the airline's daily schedule. To achieve this, an efficient solution methodology employing a heuristic-based approach has been devised. The methodology integrates two key components: a randomized search employing a Simulated Annealing algorithm, and a pseudo-gradient search procedure. By combining these elements, the methodology effectively evaluates the capacity adequacy in various airport-pairs by employing the Expected Marginal Profit as a metric. This metric serves as a reliable measure to assess the profitability of different flight frequencies. To demonstrate the effectiveness of the proposed methodology, a comparative analysis is conducted by assessing the estimated profitability of the existing flight frequency for selected airlines, against the profitability achieved by the flight frequency generated through the implementation of the proposed methodology. Through a series of experiments, the developed framework showcases its capability in determining capacity allocation strategies that result in significantly improved profitability. Overall, this research contributes to the advancement of capacity allocation methods within the airline industry, offering airlines valuable insights and actionable strategies for optimizing their operations and enhancing profitability.

Highlights • A framework for airlines near-term capacity adjustment. • Adopting the expected marginal profit as a measure for evaluating the capacity adequacy. • Modeling competition and associated demand shift. • Satisfying resources and fleet conservation constraints at the different stations. • Application to major airlines with tractable computation.