Robust algorithms for sorting railway cars
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part I
Polyhedral and algorithmic properties of quantified linear programs
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part I
A scenario-based approach for robust linear optimization
TAPAS'11 Proceedings of the First international ICST conference on Theory and practice of algorithms in (computer) systems
Quantified linear programs: a computational study
ESA'11 Proceedings of the 19th European conference on Algorithms
Experimental evaluation of approximation and heuristic algorithms for sorting railway cars
SEA'10 Proceedings of the 9th international conference on Experimental Algorithms
Information Sciences: an International Journal
A Lagrangian Heuristic for Robustness, with an Application to Train Timetabling
Transportation Science
Railway Rolling Stock Planning: Robustness Against Large Disruptions
Transportation Science
Robust planning of airport platform buses
Computers and Operations Research
Robust optimization in the presence of uncertainty
Proceedings of the 4th conference on Innovations in Theoretical Computer Science
| Hi-index | 0.00 |
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.