Airline crew rostering problem using particle swarm optimization

The issue of effective Airline crew rostering problem has been an ongoing issue for airline operation and many studies have tried to investigate and find ways to improve the crew rostering application. Airline crew rostering is a process to generate a timetable for crew members which is aligned with Occupational Health and Safety Policies. A fair and sensible roster can help to improve service quality and crew´s enthusiasm. The main objective of this paper is to propose a particle swarm optimization to solve the airline crew rostering problem by assigning appropriate balance workload for each crew member. The proposed method has been tested on real data from Thai Airways. Computational performance of the proposed method is presented and analyzed. The results are to show that the new method is effective.