Abstract
Airline profits are significantly influenced by competitive timetables that match passenger demand to fleet resources. In this research, we develop an integrated, mixed-integer optimization model to derive a comprehensive flight schedule, fleet assignment, and average airfares jointly. Passenger choice behavior is incorporated through a prospect theory-adjusted, nested, multinomial logit model which estimates market share. The competitive fleet assignment and schedule design (CFSD) formulation is embedded in a differentiated Bertrand game, such that each transport operator optimizes their best response function connected through the market share model. To solve the integrated optimization problem efficiently, a hybrid algorithm is developed that combines stabilized column generation with a large neighborhood search algorithm. The game-theoretic framework is applied to a case study in China involving legacy airlines, a low-cost carrier, and a high-speed rail (HSR) operator. The equilibrium outcomes suggest that the low-cost carrier is likely to stimulate demand and improve the level of service through secondary airports. The further development of high-speed rail service is expected to intensify competition among airlines and reduce the overall fare level. The low-cost carriers and HSR are able to significantly increase overall consumer surplus, providing insights into the potential for low-cost service in the Chinese aviation markets and the entrance of the public service obligation program at minimum cost.
Original language | English |
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Pages (from-to) | 32-50 |
Number of pages | 19 |
Journal | European Journal of Operational Research |
Volume | 314 |
Issue number | 1 |
DOIs | |
State | Published - 1 Apr 2024 |
Keywords
- Airline scheduling
- Column generation
- Non-cooperative game
- Prospect theory
All Science Journal Classification (ASJC) codes
- Information Systems and Management
- General Computer Science
- Modelling and Simulation
- Management Science and Operations Research