Adaptive Partition-based SDDP Algorithms for Multistage Stochastic Linear Programming
Optimization and Control
2019-08-30 v1 Computational Engineering, Finance, and Science
Abstract
In this paper, we extend the adaptive partition-based approach for solving two-stage stochastic programs with fixed recourse to the multistage stochastic programming setting. The proposed algorithms integrate the adaptive partition-based strategy with a popular approach for solving multistage stochastic programs, the stochastic dual dynamic programming, via different tree-traversal strategies in order to enhance its computational efficiency. Our numerical experiments on a hydro-thermal power generation planning problem show the effectiveness of the proposed algorithms.
Cite
@article{arxiv.1908.11346,
title = {Adaptive Partition-based SDDP Algorithms for Multistage Stochastic Linear Programming},
author = {Murwan Siddig and Yongjia Song},
journal= {arXiv preprint arXiv:1908.11346},
year = {2019}
}
Comments
27 pages, 6 figures