Approximate Dynamic Programming for Storage Problems
Abstract
Storage problems are an important subclass of stochastic control problems. This paper presents a new method, approximate dynamic programming for storage, to solve storage problems with continuous, convex decision sets. Unlike other solution procedures, ADPS allows math programming to be used to make decisions each time period, even in the presence of large state variables. We test ADPS on the day ahead wind commitment problem with storage.
Cite
Text
Hannah and Dunson. "Approximate Dynamic Programming for Storage Problems." International Conference on Machine Learning, 2011.Markdown
[Hannah and Dunson. "Approximate Dynamic Programming for Storage Problems." International Conference on Machine Learning, 2011.](https://mlanthology.org/icml/2011/hannah2011icml-approximate/)BibTeX
@inproceedings{hannah2011icml-approximate,
title = {{Approximate Dynamic Programming for Storage Problems}},
author = {Hannah, Lauren and Dunson, David B.},
booktitle = {International Conference on Machine Learning},
year = {2011},
pages = {337-344},
url = {https://mlanthology.org/icml/2011/hannah2011icml-approximate/}
}