An enhanced rostering model for airline crews

This paper introduces an eecient adaptation of the branch-and-bound technique that solves real-world rostering problems for airline crews. The eeciency of the algorithm is based on the exploitation of rostering-speciic properties (e.g. variable selection, branching strategy and cutting-planes), an approach that shortens the solution process and outperforms standard techniques. Furthermore, we formally introduce a general concept of downgrading that makes it possible to solve certain rostering problems that might otherwise have no solution. This paper also computes a sample monthly schedule on the basis of a medium-sized European airline's real data. Scheduling cabin and cockpit crews and their assignment to ights are important and diicult planning functions that most airlines undertake on a monthly basis. These are important tasks, given that crew costs are the highest factors of direct operational cost besides fuel. The diiculty of these tasks lies in the fact, that they refer to large-scale, complex problems that incorporate numerous regulative requirements and collective bargaining agreements. Solving a rostering problem includes the construction of individualized schedules that take into account various pre-assignments (like training or observer ights) as well as crew-requests (like days-oo or preferred ights). Using real data from a medium-sized European airline we demonstrate that our approach generates eecient solutions.