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.
This work was partially supported by the Future and Emerging Technologies Unit of EC, under contract no. FP6-021235-2 (FP6 IST/FET Open/Project ARRIVAL).
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Liebchen, C., Lübbecke, M., Möhring, R., Stiller, S. (2009). The Concept of Recoverable Robustness, Linear Programming Recovery, and Railway Applications. In: Ahuja, R.K., Möhring, R.H., Zaroliagis, C.D. (eds) Robust and Online Large-Scale Optimization. Lecture Notes in Computer Science, vol 5868. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05465-5_1
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DOI: https://doi.org/10.1007/978-3-642-05465-5_1
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