Approximate stochastic dynamic programming for hydroelectric production planning
| Autor: | Pascal Côté, Bernard F. Lamond, Luckny Zéphyr, Pascal Lang |
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| Rok vydání: | 2017 |
| Předmět: |
Mathematical optimization
021103 operations research Information Systems and Management General Computer Science Computation 0208 environmental biotechnology 0211 other engineering and technologies 02 engineering and technology Management Science and Operations Research Industrial and Manufacturing Engineering Stochastic programming 020801 environmental engineering Dynamic programming Production planning Hydroelectricity Modeling and Simulation Bellman equation Partition (number theory) Curse of dimensionality Mathematics |
| Zdroj: | European Journal of Operational Research. 262:586-601 |
| ISSN: | 0377-2217 |
| DOI: | 10.1016/j.ejor.2017.03.050 |
| Popis: | This paper presents a novel approach for approximate stochastic dynamic programming (ASDP) over a continuous state space when the optimization phase has a near-convex structure. The approach entails a simplicial partitioning of the state space. Bounds on the true value function are used to refine the partition. We also provide analytic formulae for the computation of the expectation of the value function in the “uni-basin” case where natural inflows are strongly correlated. The approach is experimented on several configurations of hydro-energy systems. It is also tested against actual industrial data. |
| Databáze: | OpenAIRE |
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