Airline crew pairing problem: Genetic and hybrid algorithms

The airline industry deals with many optimization problems such as flight and crew scheduling, fleet assignment and aircraft routing. As the crew expenses are the largest controllable component in airline companies? payments, crew schelduling is the most studied one among forementioned problems. To find effective and low cost crew schedules, many models are proposed in the literature. Many of these models divide the problem into two as crew pairing and crew rostering.In this study, a crew pairing problem that focuses on covering all the flights at the flight schedule and selecting the low cost crew pairing set is solved. Tree approaches, which are randomly generated optimization algorithm, genetic algorithm based approach and hybrid column generation approach, are developed. To compare the efficiency of the developed algorithms, a column generation approach which is commonly used in literature is prefered. Two different problem sets are used to test the performance of the algorithms and the solutions are demonstrated.