A Network Flow Approach to Crew Scheduling Based on an Analogy to an Aircraft/Train Maintenance Routing Problem
Airlines’ and railways’ expensive resources, especially crews and aircraft or trains are to be optimally scheduled to cover flights or trips of timetables. Aircraft and trains require regular servicing. They are to be routed as to regularly pass through one of the few maintenance bases, e.g., every three to four operation days for inspection. Apart from complicating workrules, crews are to be scheduled so as to “pass through” their home bases weekly for a two-day rest. This analogy is utilized in order to recognize opportunities for integrating classical planning processes for crew scheduling, and to transfer solution methodologies. A mixed-integer flow model based on a state-expanded aggregated time-space network is developed. This mathematical model, used to solve large-scale maintenance routing problems for German Rail’s intercity trains, is extended to the airline crew scheduling problem where maintenance states are replaced by crew states. The resulting network flow approach to an integrated crew scheduling process involving multiple crew domiciles and various crew requests is tested with problems from a European airline. A decision support system and computational results are presented.
Unable to display preview. Download preview PDF.
- Borndörfer, R. (1998). Aspects of Set Packing, Partitioning, and Covering. Shaker, Aachen. PhD thesis.Google Scholar
- Carl, G. and T. Gesing (2000). Flugplanung als Instrument des Informationsmanagements zur Ressourcenplanung und-Steuerung einer Linienfluggesellschaft. In J.R. Daduna and S. Voß (Eds.), Informationsmanagement im Verkehr, Physica, Heidelberg, 167–198.Google Scholar
- Darby-Dowman, K. and G. Mitra (1985). An extension of set partitioning with application to crew scheduling. European Journal of Operational Research 72, 312–322.Google Scholar
- Desrosiers, J., Y. Dumas, M.M. Solomon, and F. Soumis (1995). Time constrained routing and scheduling. In M.O. Ball, T.L. Magnanti, C.L. Monma, and G.L. Nemhauser (Eds.), Network Routing, Handbooks in Operations Research and Management Science, 8, Elsevier, Amsterdam, 35–139.Google Scholar
- El-Darzi, E. and G. Mitra (1992). Solution of set-covering and set-partitioning problems using assignment relaxations. Journal of the Operational Research Society 43, 483–493.Google Scholar
- Löbel, A. (1998). Optimal Vehicle Scheduling in Public Transit. Shaker, Aachen. PhD thesis.Google Scholar
- Mellouli, T. (1998). Periodic maintenance routing of German rail’s intercity trains by a flow model based on a state-expanded aggregated time-space network. In 6th Meeting of the EURO WG on Transportation, Gothenburg, Sweden, September 9–11, 1998. To appear in Transportation Research.Google Scholar
- Suhl, L. (1995). Computer-Aided Scheduling: An Airline Perspective. Deutscher Universitäts-Verlag, Wiesbaden.Google Scholar
- Suhl, L. and T. Mellouli (1999). Requirements for, and design of, an operations control system for railways. In N.H.M. Wilson (Ed.), Computer-Aided Transit Scheduling, Lecture Notes in Economics and Mathematical Systems, 471, Springer, Berlin, 371–390.Google Scholar