Robust airline crew pairing optimization for short-haul flights

Abstract: Crew costs are the second highest costs for airlines therefore they represent a key factor for an airline survival and crew scheduling is one of the hardest combinatorial problem. The scheduling process is broken down into crew pairing and crew rostering and, in this thesis, a robust solution is described in detail for the former one. The purpose of the thesis is to present an efficient and robust crew pairing optimization tool which minimizes the pairings costs and reduces unnecessary overcovers. The model framework is based on a new concept which involves four stages. During the first stage all roundtrip combinations are generated then in the second stage the roundtrips generated are optimized and the optimal solution is used in the third stage to generate all pairing combinations. And the last one, the fourth stage, optimizes the pairings obtained from the third stage. An augmented set covering problem is used to for the problem formulation where the unknown variables can take just integer values. A mixed integer programming solver from Google OR has been used to solve the optimization problem. In the last chapter numerical results are presented which show the efficiency of using this model framework.