Robust and Online Large-Scale Optimization

Volume 5868 of the series Lecture Notes in Computer Science pp 1-27

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

  • Christian LiebchenAffiliated withTechnische Universität Berlin
  • , Marco LübbeckeAffiliated withTechnische Universität Berlin
  • , Rolf MöhringAffiliated withTechnische Universität Berlin
  • , Sebastian StillerAffiliated withTechnische Universität Berlin

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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.