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.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.