On the impact of deep learning-based time-series forecasts on multistage stochastic programming policies
Author:
Affiliation:
1. Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
2. Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, ON, Canada
Funder
LG SciencePark
Publisher
Informa UK Limited
Subject
Computer Science Applications,Information Systems,Signal Processing
Link
https://www.tandfonline.com/doi/pdf/10.1080/03155986.2021.2015825
Reference46 articles.
1. BFC, A branch-and-fix coordination algorithmic framework for solving some types of stochastic pure and mixed 0–1 programs
2. Sampling Scenario Set Partition Dual Bounds for Multistage Stochastic Programs
3. Scenario-free stochastic programming with polynomial decision rules
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