Airlines routinely use analytics tools to support flight scheduling, fleet assignment, revenue management, crew scheduling, and many other operational decisions. However, decision support systems are less prevalent to support strategic planning. This paper fills that gap with an original mixed-integer non-convex optimization model, named Airline Network Planning with Supply and Demand interactions (ANPSD). The ANPSD optimizes network planning (including route selection, flight frequencies and fleet composition), while capturing interdependencies between airline supply and passenger demand. We first estimate a demand model as a function of flight frequencies and network configuration, using a two-stage least-squares procedure fitted to historical data, and then formalize the ANPSD by integrating the empirical demand function into an optimization model. The model is formulated as a non-convex mixed-integer program. To solve it, we develop an exact cutting plane algorithm, named 2αECP, which iteratively generates hyperplanes to develop an outer approximation of the non-linear demand functions. Computational results show that the 2αECP algorithm outperforms state-of-the-art benchmarks and generates tight solution quality guarantees. A case study based on the network of a major European carrier shows that the ANPSD provides much stronger solutions than baselines that ignore – fully or partially – demand–supply interactions.

(2021). Airline Network Planning: Mixed-integer non-convex optimization with demand–supply interactions [journal article - articolo]. In TRANSPORTATION RESEARCH PART B-METHODOLOGICAL. Retrieved from http://hdl.handle.net/10446/203674

Airline Network Planning: Mixed-integer non-convex optimization with demand–supply interactions

Birolini, Sebastian;Cattaneo, Mattia;
2021

Abstract

Airlines routinely use analytics tools to support flight scheduling, fleet assignment, revenue management, crew scheduling, and many other operational decisions. However, decision support systems are less prevalent to support strategic planning. This paper fills that gap with an original mixed-integer non-convex optimization model, named Airline Network Planning with Supply and Demand interactions (ANPSD). The ANPSD optimizes network planning (including route selection, flight frequencies and fleet composition), while capturing interdependencies between airline supply and passenger demand. We first estimate a demand model as a function of flight frequencies and network configuration, using a two-stage least-squares procedure fitted to historical data, and then formalize the ANPSD by integrating the empirical demand function into an optimization model. The model is formulated as a non-convex mixed-integer program. To solve it, we develop an exact cutting plane algorithm, named 2αECP, which iteratively generates hyperplanes to develop an outer approximation of the non-linear demand functions. Computational results show that the 2αECP algorithm outperforms state-of-the-art benchmarks and generates tight solution quality guarantees. A case study based on the network of a major European carrier shows that the ANPSD provides much stronger solutions than baselines that ignore – fully or partially – demand–supply interactions.
articolo
Birolini, Sebastian; Jacquillat, Alexandre; Cattaneo, Mattia; Pais Antunes, Antonio
(2021). Airline Network Planning: Mixed-integer non-convex optimization with demand–supply interactions [journal article - articolo]. In TRANSPORTATION RESEARCH PART B-METHODOLOGICAL. Retrieved from http://hdl.handle.net/10446/203674
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/203674
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