Advertisement

A Decision Support System for Airline Crew Management: Crew Scheduling and Rescheduling

  • Yufeng Guo
  • Leena Suhl
  • Markus P. Thiel

Abstract

We propose a decision support system that covers the complete life cycle of the airline crew scheduling process. A tool has been designed to meet the requirements for both planning and operational phase. We develop a general infrastructure for the crew management tasks in which alternative solution methods, such as mathematical programming and heuristics, can be easily incorporated. Besides the conventional two-phase scheduling (crew pairing and crew assignment) in the planning phase, the focus of our research lies on a partially integrated approach including an extension for the consideration of teams during the assignment step. For daily operations, we suggest a dedicated crew recovery approach to handle unexpected disruptions. A test case is presented to illustrate the system’s capabilities in solving a real-life problem for a medium-sized European airline.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Barnhart C, Johnson EL, Nemhauser GL, Vance PH (1999) Crew scheduling. In: Hall RW (ed) Handbook of Transportation Science. Kluwer Academic Publishers, pp 493–521Google Scholar
  2. El Moudani W, Cosenza C, de Coligny M, Mora-Camino F (2001) A bi-criterion approach for the airline crew rostering problem. In: Zitzler et al. (eds) Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization (EMO 2001). Springer, Berlin, pp 486–500Google Scholar
  3. Fahle T, Junker U, Karisch S, Kohl N, Sellmann M, Vaaben B, (2002) Constraint programming based column generation for crew assignment. Journal of Heuristics 8: 59–81CrossRefGoogle Scholar
  4. Gamache M, Soumis F (1998) A method for optimally solving the rostering problem. In Yu G (ed) Operations Research in the Airline Industry, pp 124–157Google Scholar
  5. Guo Y, Mellouli T, Suhl L, Thiel MP, (2003) A partially integrated airline crew scheduling approach with time-dependent crew capacities and multiple home bases. Tech. rep. WP0303, DS&OR Lab., University of Paderborn, Germany. Accepted by European Journal of Operational Research, Special Issue: New Opportunities in Operations ResearchGoogle Scholar
  6. Guo Y (2004) A decision support framework for the airline crew schedule disruption management with strategy mapping. Tech. rep. WP0413, DS&OR Lab., University of Paderborn, Germany. Accepted for Proceedings of Operations Research 2004 (OR2004), Tilburg, NetherlandsGoogle Scholar
  7. Kohl N and Karisch SE (2004) Airline crew rostering: problem types, modeling, and optimization. Annals of Operations Research 127: 223–257CrossRefGoogle Scholar
  8. Lettovský L, Johnson EL, Nemhauser GL (2000) Airline crew recovery. Transportation Science 34(4): 337–348Google Scholar
  9. Mellouli T (2001) A network flow approach to crew scheduling based on an analogy to a train/aircraft maintenance routing problem. In: Voß S, Daduna J (eds) Computer-Aided Scheduling of Public Transport, Lecture Notes in Economics and Mathematical Systems vol 505. Springer, Berlin, pp 91–120Google Scholar
  10. Stojković M, Soumis F, Desrosiers J (1998) The operational airline crew scheduling problem. Transportation Science 32(3): 232–245.Google Scholar
  11. Suhl L (1995) Computer-aided scheduling-an airline perspective. Deutscher Universitäts-Verlag (DUV), WiesbadenGoogle Scholar
  12. Thiel MP (2004) Team-oriented airline crew rostering for cockpit personnel. Tech. rep. WP0406, DS&OR Lab., University of Paderborn, Germany. Presented at 9th International Conference on Computer-Aided Scheduling of Public Transportation (CASPT 2004), San Diego, CAGoogle Scholar
  13. Yu G, Argüello M, Song G, McCowan SM, White A (2003) A new era for crew recovery at Continental Airlines. Interfaces 33: 5–22CrossRefGoogle Scholar

Copyright information

© Physica-Verlag Heidelberg 2005

Authors and Affiliations

  • Yufeng Guo
    • 1
  • Leena Suhl
    • 1
  • Markus P. Thiel
    • 1
  1. 1.Decision Support & Operations Research Laboratory in cooperation with International Graduate School of Dynamic Intelligent SystemsUniversity of PaderbornPaderborn

Personalised recommendations