Solving Wasserstein Robust Two-stage Stochastic Linear Programs via Second-order Conic Programming

2021 ◽  
Author(s):  
Zhuolin Wang ◽  
Keyou You ◽  
Shiji Song ◽  
Yuli Zhang
Keyword(s):  
Second Order ◽  
Conic Programming ◽  
Linear Programs ◽  
Two Stage ◽  
Stochastic Linear Programs

scholarly journals Robust two-stage stochastic linear programs with moment constraints

Optimization ◽  
2014 ◽  
Vol 63 (6) ◽  
pp. 829-837 ◽  
Author(s):  
Sarah Y. Gao ◽  
Lingchen Kong ◽  
Jie Sun
Keyword(s):  
Linear Programs ◽  
Two Stage ◽  
Stochastic Linear Programs

scholarly journals A Second-Order Sufficient Optimality Condition for Risk-Neutral Bi-level Stochastic Linear Programs

2020 ◽  
Author(s):  
Matthias Claus
Keyword(s):  
Optimality Condition ◽  
Linear Models ◽  
Sufficient Conditions ◽  
Strong Stability ◽  
Second Order ◽  
Linear Programs ◽  
Sufficient Optimality Condition ◽  
Lipschitz Continuous ◽  
Risk Neutral ◽  
Stochastic Linear Programs

Abstract The expectation functionals, which arise in risk-neutral bi-level stochastic linear models with random lower-level right-hand side, are known to be continuously differentiable, if the underlying probability measure has a Lebesgue density. We show that the gradient may fail to be local Lipschitz continuous under this assumption. Our main result provides sufficient conditions for Lipschitz continuity of the gradient of the expectation functional and paves the way for a second-order optimality condition in terms of generalized Hessians. Moreover, we study geometric properties of regions of strong stability and derive representation results, which may facilitate the computation of gradients.

Adaptive multicut aggregation for two-stage stochastic linear programs with recourse

2010 ◽  
Vol 206 (2) ◽  
pp. 395-406 ◽  
Author(s):  
Svyatoslav Trukhanov ◽  
Lewis Ntaimo ◽  
Andrew Schaefer
Keyword(s):  
Linear Programs ◽  
Two Stage ◽  
Stochastic Linear Programs
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