Solving the Aircraft Sequencing Problem Using Concurrent Constraint Programming

  • Juan Francisco Díaz
  • Javier Andrés Mena
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3389)


In this paper we describe an application that solves the problem of aircraft sequencing in airports using a single runway. In this problem, the air traffic controller must compute a landing (take off) time for each plane in the horizon or airport. The cost is associated with the difference between the plane preferred time (for landing or taking off) and the time assigned to it. There is also a minimum separation time between planes that must be respected to avoid accidents. We have implemented an application using Mozart with finite domain constraints, GUIs to interact with the user, and a propagator with a simple, but very helpful operation to cut domains. The basis of the application is the engine that implements the model of the problem; it is easily extensible through the implementation of new distributors. This paper shows how the powerful features of Mozart could be exploited to implement practical applications.


Search Tree Prefer Time Distribution Strategy Target Time Strong Propagation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Baptiste, P., Le Pape, C., Nuijten, W.: Incorporating efficient operations research algorithms in constraint-based scheduling. In: 1st International Joint Workshop on Artificial Intelligence and Operations Research, Timberline Lodge, Oregon (1995)Google Scholar
  2. 2.
    Beasley, J.E.: Or-library: distributing problems by electronic mail. Journal of the Operations Research Society 41, 1069–1072 (1990)Google Scholar
  3. 3.
    Beasley, J.E., Krishnamoorthy, M., Sharaiha, Y.M., Abramson, D.: Scheduling aircraft landings–the static case. Transportation Science 34(2), 180–197 (2000)zbMATHCrossRefGoogle Scholar
  4. 4.
    Fahle, T., Feldmann, R., Götz, S., Grothklags, S., Monien, B.: The aircraft sequencing problem. In: Computer science in perspective, pp. 152–166. Springer, New York (2003)CrossRefGoogle Scholar
  5. 5.
    Jung, G., Laguna, M.: Time segmentation heuristic for an aircraft landing problem, March 6 (2003)Google Scholar
  6. 6.
    Krishnamoorthy, M., Ernst, A.T.: Scheduling aircraft landings optimally. In: Proceedings of the 41st Annual Symposium of AGIFORS, Sydney, Australia, August 27 –September 1 (2001)Google Scholar
  7. 7.
    Mullings, J.: Trails of destruction. New Scientist (1996)Google Scholar
  8. 8.
    Silva, D., Mills, G., Abela, J., Krishnamoorthy, K.: Computing optimal schedules for landing aircraft, October 19 (1995)Google Scholar
  9. 9.
    Trani, A.A., Martinez, J., Baik, H., Kamat, V.: A new paradigm to model aircraft operations at airports: The virginia tech airport simulation model (vtasim). In: NEXTOR Research Symposium, November 13 (2000)Google Scholar
  10. 10.
    van Leeuwen, P., Hesselink, H., Rohling, J.: Scheduling aircraft using constraint satisfaction. In: Electronic Notes in Theoretical Computer Science, vol. 76. Elsevier, Amsterdam (2002)Google Scholar
  11. 11.
    Van Roy, P., Haridi, S.: Mozart: A programming system for agent applications. In: International Workshop on Distributed and Internet Programming with Logic and Constraint Languages, Part of International Conference on Logic Programming (ICLP 1999) (November 1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Juan Francisco Díaz
    • 1
  • Javier Andrés Mena
    • 1
  1. 1.Escuela de Ingeniería de Sistemas y ComputaciónUniversidad del ValleCaliColombia

Personalised recommendations