Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Solving airline crew scheduling problems by branch-and-cut
Management Science
Flight graph based genetic algorithm for crew scheduling in airlines
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on evolutionary algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Real-World Applications of Evolutionary Computing, EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoROB, and EvoFlight
Parallel Algorithms for Airline Crew Planning on Networks of Workstations
ICPP '98 Proceedings of the 1998 International Conference on Parallel Processing
A Heuristic Method for the Set Covering Problem
Operations Research
Impact of heterogeneity on the deployment of sensor networks
WICON '07 Proceedings of the 3rd international conference on Wireless internet
Crew pairing optimization based on hybrid approaches
Computers and Industrial Engineering
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We present an algorithm for the crew pairing problem, an optimization problem that is part of the airline crew scheduling procedure. A pairing is a round trip starting and ending at the home base, which is susceptible to constraints that arise due to laws and regulations. The purpose of the crew pairing problem is to generate a set of pairings with minimal cost, covering all flight legs that the company has to carry out during a predefined time period. The proposed solution is a two-phase procedure. For the first phase, the pairing generation, a depth first search approach is employed. The second phase deals with the selection of a subset of the generated pairings with near optimal cost. This problem, which is modelled by a set covering formulation, is solved with a genetic algorithm. The presented method was tested on actual flight data of Olympic Airways.