英文摘要 |
Airline cabin crew scheduling problems have been traditionally formulated as set covering problems or set partitioning problems. To resolve large-scale problems in practice, the column generation approach with integer programming algorithms has usually been employed in decades. When airline carries face the the multi base operations as well as aircraft type continuity and cabin classes in practical operations, these problems become more complicated and difficult to solve. In this research, taking into account the aforementioned factors, we introduce a new network modelthat can improve both efficiencyand and effectiveness of solving cabin crew scheduling problems to help air carriers minimize crew cost and plan proper crew service rotations under the real constraints. Mathematically, the model is formulated as a multi-commodity network flow problem. A Lagrangian relaxation-based algorithm, coupled with a subgradient method, the network simplex method and a heuristic for upper bound solution, is suggested to solve the problem. Furthermore, the flow decomposition algorithm is applied to generate all pairings for cabin crews. In order to evaluate the model in practice, computational tests referring the international operation of a major airline in Taiwan were performed. The results show the networkmodel and the Lagrangian relaxation-based algorithm can be useful for efficiently solving large-scale airline cabin crew scheduling problems. |