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From State-of-the-Art Static Fleet Assignment to Flexible Stochastic Planning of the Future

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Algorithmics of Large and Complex Networks

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5515))

Abstract

Given a flight schedule, which is a set of non-stop flights, called legs, with specified departure and arrival times, and a set of aircraft types, called subfleets, the fleet assignment problem is to determine which aircraft type should fly each leg. The objective is to maximize the overall profit.

Usually, planners assume that precise input data are determininstically available at planning time. As a consequence, an important insufficiency of modern industrial plans, especially flight-plans, is their lack of robustness. Disruptions prevent from operating as planned before and induce high costs for trouble shooting.

One reason for the uncertainties in the data for fleet assignment is that this problem is part of a long row of optimization problems of an airline. Therefore, important restrictions of later steps like connection dependent ground times should be considered in the fleet assignment problem. We show how connection dependent ground times can be added to the fleet assignment problem and presents three optimization methods, varying in run time and solution quality, that can solve real-world problem instances with more than 6000 legs within minutes.

Moreover, real or believed non-determinism leads to inevitable uncertainties in input data. As a consequence, instead of a traditional plan, a flexible strategy which reacts on different relizations of the uncertain data is demanded. The Repair Game is a formalization of a planning task, and playing it performs disruption management and generates robust plans with the help of game tree search. We introduce the game and present experimental results of a feasibility study.

This work has been partially supported by the European Union within the 6th Framework Program under contract 001907 (DELIS) and the German Science Foundation (DFG), SFB 614 (Selbstoptimierende Systeme des Maschinenbaus) and SPP 1126 (Algorithmik großer und komplexer Netzwerke).

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Author information

Authors and Affiliations

  1. Lufthansa Systems Berlin GmbH Airline Planning & Control, Salzufer 8, D-10587, Germany

    Sven Grothklags

  2. Institute of Mathematics, Darmstadt University of Technology, Schlossgartenstr. 7, D-64289, Darmstadt, Germany

    Ulf Lorenz

  3. Faculty of Computer Science, Electrical Engineering and Mathematics, University of Paderborn, Fürstenallee 11, D-33102, Paderborn, Germany

    Burkhard Monien

Authors
  1. Sven Grothklags
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  2. Ulf Lorenz
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  3. Burkhard Monien
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Editor information

Editors and Affiliations

  1. Department of Computer & Information Science, University of Konstanz, 78457, Konstanz, Germany

    Jürgen Lerner

  2. Institute of Theoretical Informatics, Technical University of Karlsruhe, 76128, Karlsruhe, Germany

    Dorothea Wagner

  3. Department of Biological Physics, Eötvös Lorand University, Pazmany P. Stny 1A, 1117, Budapest, Hungary

    Katharina A. Zweig

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Grothklags, S., Lorenz, U., Monien, B. (2009). From State-of-the-Art Static Fleet Assignment to Flexible Stochastic Planning of the Future. In: Lerner, J., Wagner, D., Zweig, K.A. (eds) Algorithmics of Large and Complex Networks. Lecture Notes in Computer Science, vol 5515. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02094-0_8

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  • DOI: https://doi.org/10.1007/978-3-642-02094-0_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02093-3

  • Online ISBN: 978-3-642-02094-0

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