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Air traffic flow management with heuristic repair

Published online by Cambridge University Press:  26 July 2012

Ulrich Junker
Ulrich Junker*
Affiliation:
ILOG, 1681, route des Dolines, F-06560 Valbonne, France; e-mail: uli.junker@free.fr
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Abstract

The European air traffic flow management problem poses particular challenges on optimization technology as it requires detailed modelling and rapid online optimization capabilities. Constraint programming proved successful in addressing these challenges for departure time slot allocation by offering fine-grained modelling of resource constraints and fast allocation through heuristic-repair strategies.

Type
Articles
Information
The Knowledge Engineering Review , Volume 27 , Special Issue 3: Constraint Programming for Air Traffic Management , 26 July 2012 , pp. 333 - 342
Copyright
Copyright © Cambridge University Press 2012

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References

Barnier, N., Brisset, P., Rivière, T. 2001. Slot allocation with constraint programming: models and results. In International Air Traffic Management R&D Seminar ATM-2001. Santa Fe (NM), USA.Google Scholar
Bertsimas, D., Lulli, G., Odoni, A. R. 2008. The air traffic flow management problem: an integer optimization approach. In Proceedings of the IPCO, 34–46. Bertinoro, Italy.CrossRefGoogle Scholar
Bertsimas, D., Stock, S. 1994. The Air Traffic Flow Management Problem with Enroute Capacities. MIT-report. MIT.Google Scholar
Chevaleyre, Y., Endriss, U., Lang, J., Maudet, N. 2007. A short introduction to computational social choice. In Proceedings of the SOFSEM 2007: Theory and Practice of Computer Science, 51–69. Springer.CrossRefGoogle Scholar
Central Flow Management Unit. 2009. Basic CFMU Handbook—General & CFMU Systems, 13.0 edition . Eurocontrol CFMU.Google Scholar
Dalichampt, M., Petit, E., Junker, U., Lebreton, J. 1997. Innovative Slot Allocation. Executive summary of EEC report no. 322, Eurocontrol Experimental Centre.Google Scholar
Flener, P., Pearson, J., Agren, M., Garcia-Avello, C., Celiktin, M., Dissing, S. 2007. Air-traffic complexity resolution in multi-sector planning. Journal of Air Transport Management 13, 323–328.CrossRefGoogle Scholar
Harvey, W.D., Ginsberg, M.L. 1995. Limited discrepancy search. In, Proceedings of IJCAI, 607–615. Montreal, Quebec, Canada.Google Scholar
Junker, U. 2007. Preference-based problem solving for constraint programming. In Proceedings of the CSCLP 2007, 109–126. Rocquencourt, France.CrossRefGoogle Scholar
Minton, S., Johnston, M.D., Philips, A.B., Laird, P. 1992. Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling. Artificial Intelligence 58, 161–205.CrossRefGoogle Scholar
Rossi, F., van Beek, P., Walsh, T. 2006. The Handbook of Constraint Programming. Elsevier.Google Scholar
Wolsey, L.A., Nemhauser, G.L. 1999. Integer and Combinatorial Optimization. Wiley.Google Scholar