Risk-Averse Optimization in Two-Stage Stochastic Models: Computational Aspects and a Study
Risk-Averse Optimization in Two-Stage Stochastic Models: Computational Aspects and a Study
复制标题
两阶段随机模型中的风险规避优化：计算方面和研究
作者：
Csaba I. Fábián;Christian Wolf;Achim Koberstein;L. Suhl
我们将Oliveira和Sagastizabal的按需精度方法扩展到约束凸优化。所得到的方法适用于风险厌恶的两阶段随机规划问题。我们提出了一个风险厌恶模型的调查。适当的甲骨文制定的情况下，有条件的风险价值约束。我们讨论了计算方面，并在一项研究中比较不同的方法。
We extend the on-demand accuracy approach of Oliveira and Sagastizabal to constrained convex optimization. The resulting method is applied to risk-averse two-stage stochastic programming problems. We present a survey of risk-averse models. The appropriate oracle is formulated for the case of a conditional value-at-risk constraint. We discuss computational aspects and compare different approaches in a study.