Journal of Computer and System Sciences
Approximation algorithms for NP-hard problems
Approximation algorithms for NP-hard problems
Approximation in stochastic scheduling: the power of LP-based priority policies
Journal of the ACM (JACM)
The Sample Average Approximation Method for Stochastic Discrete Optimization
SIAM Journal on Optimization
Stochastic Optimization is (Almost) as easy as Deterministic Optimization
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
Computational complexity of stochastic programming problems
Mathematical Programming: Series A and B
Production Planning by Mixed Integer Programming (Springer Series in Operations Research and Financial Engineering)
Approximation in preemptive stochastic online scheduling
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
On a decision procedure for quantified linear programs
Annals of Mathematics and Artificial Intelligence
A PTAS for Static Priority Real-Time Scheduling with Resource Augmentation
ICALP '08 Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I
From State-of-the-Art Static Fleet Assignment to Flexible Stochastic Planning of the Future
Algorithmics of Large and Complex Networks
The Concept of Recoverable Robustness, Linear Programming Recovery, and Railway Applications
Robust and Online Large-Scale Optimization
Solutions to real-world instances of PSPACE-complete stacking
ESA'07 Proceedings of the 15th annual European conference on Algorithms
Quantified linear programs: a computational study
ESA'11 Proceedings of the 19th European conference on Algorithms
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Quantified linear programs (QLPs) are linear programs with variables being either existentially or universally quantified. The integer variant is PSPACE-complete, and the problem is similar to games like chess, where an existential and a universal player have to play a two-person-zero-sum game. At the same time, a QLP with n variables is a variant of a linear program living in Rn, and it has strong similarities with multistage-stochastic programs with variable right-hand side. We show for the continuous case that the union of all winning policies of the existential player forms a polytope in Rn, that its vertices are games of so called extremal strategies, and that these vertices can be encoded with polynomially many bits. The latter allows the conclusion that solving a QLP is in PSPACE. The hardness of the problem stays unknown.