A Two-stage Decision Dependent Stochastic Approach for Airline Flight Network Expansion

Özge Şafak, University of Bath


Airlines need to expand their flight network with developing new routes and introducing more flights to increase their market share. In this work, we propose a two-stage stochastic mixed integer nonlinear program (MINLP), which expands an existing flight schedule by operating new flights either with existing fleet resources or a leased aircraft while considering the impact of departure time decisions on the probability distribution of random demand. Moreover, our study helps an airline to link a strategic decision of leasing an aircraft to the tactical aircraft assignment decisions by considering the fuel efficiency and the seat capacity of the aircraft alternatives in response to new passenger demand. However, the large number of scenarios, nonlinear fuel burn function and nonlinearities due to the decision dependent probabilities become main challenges of solving the problem. To deal with the computational requirements of a two-stage stochastic MINLP with decision dependent probabilities, we propose strong conic quadratic and McCormick inequalities, and an exact scenario group wise decomposition algorithm with a new bounding method. In our computational results, we clearly demonstrate the effectiveness of proposed decomposition algorithm and the strength of the reformulations.

This is a joint work with Prof. M. Selim Akturk and Assoc. Prof. Ozlem Cavus Iyigun.

Short Bio

Özge Şafak is currently a prize fellow at University of Bath, UK. She received her B.S. degree in Industrial Engineering from Sabanci University, Turkey in 2011. She received her M.S. and Ph.D. degrees in Industrial Engineering from Bilkent University, Turkey in 2013 and 2019, respectively. During her Ph.D. studies, she worked as a visiting research scholar in Industrial Engineering and Operations Research at University of California, Berkeley in 2017. Her research focuses on the stochastic and discrete optimization with the applications in airline scheduling and logistics.


Friday, October 7, 2022, 4.00 pm - Zoom Meeting


Announcement Category