A Greedy Heuristic for Airline Crew Rostering: Unique Challenges in a Large Airline in China

Abstract

We study a unique challenge in the crew rostering problem faced by a large airline in China, where fairness for crewmembers is the main concern. The fairness aspect of rosters produced by a commercial optimizer is not satisfactory. We discuss the challenges imposed by the fairness constraint and devise a greedy heuristic to directly address these challenges. The resulting algorithm is not only much faster but also produces a more balanced plan based on actual data from the airline in question.