Castelletti, Andrea and De Rigo, Daniele and Rizzoli, Andrea Emilio and Soncini-Sessa, Rodolfo and Weber, Enrico (2007) Neuro-dynamic programming for designing water reservoir network management policies. Control Engineering Practice, 15 (8). pp. 1031-1038.
Full text not available from this repository.Abstract
Stochastic dynamic programming (SDP) can improve the management of a multipurpose water reservoir by generating management policies which are efficient with respect to the management objectives (flood protection, water supply for irrigation, hydropower generation, etc.). The improvement in efficiency is even more remarkable for networks of reservoirs. Unfortunately, SDP is affected by the well-known ‘curse of dimensionality’, i.e. computational time and computer memory occupation increase exponentially with the dimension of the problem (number of reservoirs), and the problem rapidly becomes intractable. Neuro-dynamic programming (NDP) can sensibly mitigate this limitation by approximating Bellman functions with artificial neural networks (ANNs). In this paper the application of NDP to the problem of the management of reservoir networks is introduced. Results obtained in a real-world case study are finally presented.
| Item Type: | Scientific journal article, Newspaper article or Magazine article |
|---|---|
| Uncontrolled Keywords: | water resources management, optimisation, dynamic programming |
| Subjects: | Mathematical sciences > Operational research Engineering > Civil engineering > Environmental engineering |
| Department/unit: | Dipartimento tecnologie innovative > Istituto Dalle Molle di studi sull’intelligenza artificiale USI-SUPSI |
| Depositing User: | Andrea Emilio Rizzoli |
| Date Deposited: | 27 Feb 2014 13:50 |
| Last Modified: | 09 May 2016 14:46 |
| URI: | http://repository.supsi.ch/id/eprint/1178 |
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