Two simplex-based approximate stochastic dynamic programming schemes for a real hydropower management problem

We present an approximate stochastic dynamic programming methodology for a real-world hydropower management problem, in which water must be released from reservoirs to produce electricity to power aluminum smelters over a planning horizon of a year (three-day time step). In each period, decisions ar...

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Bibliographic Details
Published in:	Annals of operations research Vol. 351; no. 1; pp. 333 - 364
Main Authors:	Zephyr, Luckny, Lamond, Bernard F., Demeester, Kenjy, Latraverse, Marco
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.08.2025 Springer Nature B.V
Subjects:	Algorithms Apexes Approximation Artificial intelligence Business and Management Combinatorics Decomposition Dynamic programming Electricity Errors Hydroelectric power Hydrology Lower bounds Monte Carlo simulation Operations Research/Decision Theory Original Research Reservoirs Smelters Theory of Computation Water Water shortages Canada Approximate stochastic dynamic programming Simplex Stochastic dynamic programming Hydropower Monte Carlo simulation Data envelopment analysis
ISSN:	0254-5330, 1572-9338
Online Access:	Get full text
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