当前位置: X-MOL 学术SIAM J. Optim. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Distributionally Robust Stochastic Dual Dynamic Programming
SIAM Journal on Optimization ( IF 3.1 ) Pub Date : 2020-10-07 , DOI: 10.1137/19m1309602
Daniel Duque , David P. Morton

SIAM Journal on Optimization, Volume 30, Issue 4, Page 2841-2865, January 2020.
We consider a multistage stochastic linear program that lends itself to solution by stochastic dual dynamic programming (SDDP). In this context, we consider a distributionally robust variant of the model with a finite number of realizations at each stage. Distributional robustness is with respect to the probability mass function governing these realizations. We describe a computationally tractable variant of SDDP to handle this model using the Wasserstein distance to characterize distributional uncertainty.


中文翻译:

分布鲁棒随机对偶动态规划

SIAM优化杂志,第30卷,第4期,第2841-2865页,2020年1月。
我们考虑了一种多阶段随机线性程序,该程序可以通过随机双重动态规划(SDDP)解决方案。在这种情况下,我们考虑模型的分布稳健的变体,在每个阶段都有有限数量的实现。分布鲁棒性是关于控制这些实现的概率质量函数的。我们描述了使用Wasserstein距离来表征分布不确定性的SDDP的计算可处理变量,以处理该模型。
更新日期:2020-11-13
down
wechat
bug