Crew Pairing at Air France

By Guy Desaulniers, Jacques Desrosiers, Marius M. Solomon, François Soumis, Y. Dumas, S. Marc, B. Rioux. 1993

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In Optimization & Training

Citations in the corpus

Structured Convolutional Kernel Networks for Airline Crew Scheduling (2021, methodology): “The CPP has been traditionally modelled as a set partitioning problem, with a covering constraint for each flight and a variable for each feasible pairing (Desaulniers et al., 1997; Kasirzadeh et al., 2017).”
An Annotated Bibliography of Personnel Scheduling and Rostering (2004, unknown): “…1999), (Curtis et al., 2000), (Daduna and Mojsilovic, 1988), (Darby-Dowman and Mitra, 1985), (Darby-Dowman et al., 1988), (Desaulniers et al., 1999), (Desaulniers et al., 1998), (Desaulniers et al., 1997), (Desrochers and Soumis, 1989), (Desrochers and Soumis, 1988), (Desrochers et al., 1992), (?)”
Dynamic Constraint Aggregation for Solving Very Large-scale Airline Crew Pairing Problems (2020, methodology): “To achieve high-quality solutions while keeping the computational times under control for medium-sized CPP instances, a variety of column generation (CG) algorithms have been devised, including those of [1, 2, 6, 12, 23, 26, 27, 29, 30, 32, 35].”
Flight-connection Prediction for Airline Crew Scheduling to Construct Initial Clusters for OR Optimizer (2019, unknown): “In the literature, the crew pairing problem has been modeled as a set covering or a set partitioning problem, in which each column is a constraint associated with each flight and all feasible pairings are treated as variables (Desaulniers et al., 1997; Qiu, 2012; Kasirzadeh et al., 2017).”
Benders Decomposition for Simultaneous Aircraft Routing and Crew Scheduling (2000, methodology): “…was first applied to the crew pairing problem by Lavoie et al. (1988), while further developments and alternative solution methods can be found in the recent works of Hoffman and Padberg (1993), Graves et al. (1993), Barnhart et al. (1995), Vance et al. (1997), and Desaulniers et al. (1997a).”
Machine Learning in Airline Crew Pairing to Construct Initial Clusters for Dynamic Constraint Aggregation (2020, methodology): “In the literature, the CPP has been traditionally modelled as a set covering problem (SCP) or a set partitioning problem (SPP), with a covering constraint for each flight and a variable for each feasible pairing [3, 21, 22].”
Staff scheduling and rostering: A review of applications, methods and models (2004, background): “Many articles deal with airline crew pairing generation, crew pairing optimisation and crew rostering including [14,25,36,60,66,67,71,94,96,109,155,156,184].”