A HYBRID GENETIC ALGORITHM FOR AIRLINE CREW PAIRING OPTIMIZATION

Abstract

Airline operational problems associated with flight scheduling, aircraft scheduling and crew scheduling are usually solved in two phases: crew pairing and crew rostering and management of irregular operations. Each problem has its own complexities. This study examines the crew pairing problem, one of the most comprehensible problems encountered in airline planning. The study aims to generate a set of crew pairings with minimal cost, covering all flight legs and fulfilling legal criteria. Drawing from the previous studies which seek to solve the crew pairing problem through genetic algorithm, the present study proposes a hybrid genetic algorithm approach. To test the algorithm, optimal crew pairings have been generated by making use of the flight data obtained from an airline company operating in Turkey.