Integrated flight scheduling and fleet assignment with improved supply-demand interactions. (July 2021)

• Record Type: Journal Article
• Authors: Birolini, Sebastian; Antunes, António Pais; Cattaneo, Mattia; Malighetti, Paolo; Paleari, Stefano
• Is Part Of: Transportation research. Volume 149(2021)
• Page Start: 162
• Page End: 180
• Publication Date: 2021-07
• Subjects: Flight scheduling -- Fleet assignment -- Integrated airline planning -- Demand-supply interactions -- Piecewise linearization; Transportation -- Research -- Periodicals; Transportation -- Mathematical models -- Periodicals
• DOI: 10.1016/j.trb.2021.05.001
• Languages: English
• ISSNs: 0191-2615

Abstract

Highlights: Novel mixed-integer nonlinear flight scheduling and fleet assignment optimization model with supply-demand interactions. Demand generation and allocation consistently endogenized using a nested logit model. Least squares piecewise linearization method to approximate the nonlinearities. Computational experiments show the applicability of the approach to mid-size hub-and-spoke networks. A case study for a European carrier highlights the benefits of the approach compared to an inelastic market demand approach. Abstract: Flight scheduling and fleet assignment are important steps of an airline planning process. In light of the reciprocal relationship between air transport supply and demand, a key element of these models is to devise effective methods to both incorporating estimation of total market demand and allocating passengers over the available itineraries in a specific market. In this paper, we present a novel mixed integer nonlinear flight scheduling and fleet assignment optimization model wherein air travel demand generation and allocation are simultaneously and consistently endogenized. Using a nested logit formulation, we jointly model competition among air travel itineraries and appraise the contribution of specific itinerary attributes to demand generation, therefore yielding a more comprehensive and explicit representation of supply-demand interactions. Computational testing based on realistic problem instances reveals that the model can optimize mid-size hub-and-spoke networks within reasonable time. Further analyses illustrate the benefits that can be derived from the application of the proposed approach using real-world data for a major European airline. Results demonstrate that the proposed approach can significantly enhance operating profits by up to 6.9% and better reveal opportunities for demand stimulation against a conventional approach using inelastic trip generation.