A global approach to crew-pairing optimization
IBM Systems Journal
Solving airline crew scheduling problems by branch-and-cut
Management Science
Optimized Crew Scheduling at Air New Zealand
Interfaces
Solving Large Airline Crew Scheduling Problems: Random Pairing Generation and Strong Branching
Computational Optimization and Applications
Branch-And-Price: Column Generation for Solving Huge Integer Programs
Operations Research
An Approximate Model and Solution Approach for the Long-Haul Crew Pairing Problem
Transportation Science
Airline Crew Scheduling with Regularity
Transportation Science
A New Pricing Scheme for Airline Crew Scheduling
INFORMS Journal on Computing
Computers and Operations Research
Integrated Airline Crew Pairing and Crew Assignment by Dynamic Constraint Aggregation
Transportation Science
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A crew pairing is a sequence of flights, connections and rests that starts and ends at a crew base and is assigned to a single crew. The crew pairing problem consists of determining a minimum cost set of feasible crew pairings such that each flight is covered exactly once and side constraints are satisfied. Traditionally, this problem has been solved in the industry by a heuristic three-phase approach that solves sequentially a daily, a weekly, and a monthly problem. This approach prohibits or strongly penalizes the repetition of the same flight number in a pairing. In this paper, we highlight two weaknesses of the three-phase approach and propose alternative solution approaches that exploit flight number repetitions in pairings. First, when the flight schedule is irregular, we show that better quality solutions can be obtained in less computational time if the first two phases are skipped and the monthly problem is solved directly using a rolling horizon approach based on column generation. Second, for completely regular flight schedules, we show that better quality solutions can be derived by skipping the daily problem phase and solving the weekly problem directly.