Robust and Online Large-Scale Optimization pp 1-27

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5868)

The Concept of Recoverable Robustness, Linear Programming Recovery, and Railway Applications

  • Christian Liebchen
  • Marco Lübbecke
  • Rolf Möhring
  • Sebastian Stiller

Abstract

We present a new concept for optimization under uncertainty: recoverable robustness. A solution is recovery robust if it can be recovered by limited means in all likely scenarios. Specializing the general concept to linear programming we can show that recoverable robustness combines the flexibility of stochastic programming with the tractability and performances guarantee of the classical robust approach. We exemplify recoverable robustness in delay resistant, periodic and aperiodic timetabling problems, and train platforming.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Christian Liebchen
    • 1
  • Marco Lübbecke
    • 1
  • Rolf Möhring
    • 1
  • Sebastian Stiller
    • 1
  1. 1.Technische Universität BerlinBerlinGermany

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