Local epi-continuity and local optimization
Mathematical Programming: Series A and B
Stability in two-stage stochastic programming
SIAM Journal on Control and Optimization
Optimization
Distribution sensitivity in stochastic programming
Mathematical Programming: Series A and B
Stability analysis for stochastic programs
Annals of Operations Research
Stability and sensitivity-analysis for stochastic programming
Annals of Operations Research
Asymptotic theory for solutions in statistical estimation and stochastic programming
Mathematics of Operations Research
Lipschitzian stability of constraint systems and generalized equations
Nonlinear Analysis: Theory, Methods & Applications
Quantitative stability in stochastic programming
Mathematical Programming: Series A and B
Strong convexity in stochastic programs with complete recourse
Journal of Computational and Applied Mathematics
A stochastic approach to stability in stochastic programming
Journal of Computational and Applied Mathematics
A note on estimates in stochastic programming
Journal of Computational and Applied Mathematics
Applications of stochastic programming under incomplete information
Journal of Computational and Applied Mathematics
Sensitivity with respect to the underlying information in stochastic programs
Journal of Computational and Applied Mathematics
Mathematical Programming: Series A and B
Analysis of sample-path optimization
Mathematics of Operations Research
On the Glivenko-Cantelli Problem in Stochastic Programming: Linear Recourse and Extensions
Mathematics of Operations Research
Differential Stability of Two-Stage Stochastic Programs
SIAM Journal on Optimization
On the Rate of Convergence of Optimal Solutions of Monte Carlo Approximations of Stochastic Programs
SIAM Journal on Optimization
Rates of Convergence in Stochastic Programs with Complete Integer Recourse
SIAM Journal on Optimization
Scenario Reduction Algorithms in Stochastic Programming
Computational Optimization and Applications
Applying the Minimum Risk Criterion in Stochastic Recourse Programs
Computational Optimization and Applications
Stochastic Integer Programming: Limit Theorems and Confidence Intervals
Mathematics of Operations Research
Recent Advances in Reinforcement Learning
Scenario reduction in stochastic programming with respect to discrepancy distances
Computational Optimization and Applications
Algorithmic Aspects of Scenario-Based Multi-stage Decision Process Optimization
ADT '09 Proceedings of the 1st International Conference on Algorithmic Decision Theory
Mathematics of Operations Research
Evolutionary multi-stage financial scenario tree generation
EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
A note on scenario reduction for two-stage stochastic programs
Operations Research Letters
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Quantitative stability of optimal values and solution sets to stochastic programming problems is studied when the underlying probability distribution varies in some metric space of probability measures. We give conditions that imply that a stochastic program behaves stable with respect to a minimal information (m.i.) probability metric that is naturally associated with the data of the program. Canonical metrics bounding the m.i. metric are derived for specific models, namely for linear two-stage, mixed-integer two-stage and chance-constrained models. The corresponding quantitative stability results as well as some consequences for asymptotic properties of empirical approximations extend earlier results in this direction. In particular, rates of convergence in probability are derived under metric entropy conditions. Finally, we study stability properties of stable investment portfolios having minimal risk with respect to the spectral measure and stability index of the underlying stable probability distribution.