Flight scheduling and maintenance base planning
Management Science
The fleet assignment problem: solving a large-scale integer program
Mathematical Programming: Series A and B
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Branch-And-Price: Column Generation for Solving Huge Integer Programs
Operations Research
The Aircraft Maintenance Routing Problem
Operations Research
Benders Decomposition for Simultaneous Aircraft Routing and Crew Scheduling
Transportation Science
A Stochastic Model of Airline Operations
Transportation Science
Itinerary-Based Airline Fleet Assignment
Transportation Science
Airline Crew Scheduling with Time Windows and Plane-Count Constraints
Transportation Science
Improving Crew Scheduling by Incorporating Key Maintenance Routing Decisions
Operations Research
Accelerating column generation for aircraft scheduling using constraint propagation
Computers and Operations Research
An integrated aircraft routing, crew scheduling and flight retiming model
Computers and Operations Research
Computers and Operations Research
Airline Crew Scheduling Under Uncertainty
Transportation Science
A Stochastic Programming Approach to the Airline Crew Scheduling Problem
Transportation Science
Robust Airline Crew Pairing: Move-up Crews
Transportation Science
Integrated Airline Fleeting and Crew-Pairing Decisions
Operations Research
On a New Rotation Tour Network Model for Aircraft Maintenance Routing Problem
Transportation Science
On a New Rotation Tour Network Model for Aircraft Maintenance Routing Problem
Transportation Science
Solving a robust airline crew pairing problem with column generation
Computers and Operations Research
Integrated staffing and scheduling for an aircraft line maintenance problem
Computers and Operations Research
An integrated scenario-based approach for robust aircraft routing, crew pairing and re-timing
Computers and Operations Research
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In airline scheduling a variety of planning and operational decision problems have to be solved. We consider the problems aircraft routing and crew pairing: aircraft and crew must be allocated to flights in a schedule in a minimal cost way. Although these problems are not independent, they are usually formulated as independent mathematical optimisation models and solved sequentially. This approach might lead to a suboptimal allocation of aircraft and crew, since a solution of one of the problems may restrict the set of feasible solutions of the problem solved later. Also, when minimal cost solutions are used in operations, a short delay of one flight can cause very severe disruptions of the schedule later in the day. We generate solutions that incur small costs and are also robust to typical stochastic variability in airline operations. We solve the two original problems iteratively. Starting from a minimal cost solution, we produce a series of solutions which are increasingly robust. Using data from domestic airline schedules we evaluate the benefits of the approach as well as the trade-off between cost and robustness. We extend our approach considering the aircraft routing problem together with two crew pairing problems, one for technical crew and one for flight attendants.