@incollection{castellettiNeuroDynamicProgrammingEfficient2004,
  title = {Neuro-{{Dynamic Programming}} for the Efficient Integrated Water Resources Management},
  booktitle = {Modelling and Control for Participatory Planning and Managing Water Systems},
  author = {Castelletti, A. and de Rigo, D. and Rizzoli, A. E. and Soncini-Sessa, R. and Weber, E.},
  editor = {Soncini-Sessa, R.},
  date = {2004-09},
  publisher = {{Clup}},
  location = {{Italy}},
  url = {http://mfkp.org/INRMM/article/10812626},
  abstract = {Design of policies within the integrated water resources management (IWRM)

paradigm demands to take into account multiple objectives such as flood protection, water

supply for hydropower generation, irrigation and urban use, imposition of minimum environmental flows, etc.. Finding efficient water management policies is a demanding task

and Stochastic Dynamic Programming (SDP) can provide an effective solution methodology. The efficiency boost is even more pronounced when the scale of integration of the

water management problem spans networks of water resources (i.e. sets of interconnected

reservoirs, or wide-area water distribution systems). Unfortunately, SDP suffers from the

so-called ” curse of dimensionality”, that is, computational times and memory storage requirements increase exponentially with the dimension of the problem (number of reservoirs

and water diversions), and rapidly the problem becomes intractable. Neuro-dynamic programming (NDP) can sensibly mitigate both of these problems by approximating the Bell-

man functions with Artificial Neural Networks (ANNs). In this paper we present the theoretical framework of this approach and some preliminary results obtained on a real world

case study, where the NDP approach to IWRM problems has been applied to a multipurpose water reservoir network.},
  isbn = {978-88-7090-732-2},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-10812626,artificial-neural-networks,curse-of-dimensionality,integrated-water-resources-management,neuro-dynamic-programming},
  options = {useprefix=true}
}

{"_id":"pSs6Aos6uWhmKGhNu","bibbaseid":"castelletti-derigo-rizzoli-soncinisessa-weber-neurodynamicprogrammingfortheefficientintegratedwaterresourcesmanagement","authorIDs":[],"author_short":["Castelletti, A.","de Rigo, D.","Rizzoli, A. E.","Soncini-Sessa, R.","Weber, E."],"bibdata":{"bibtype":"incollection","type":"incollection","title":"Neuro-Dynamic Programming for the Efficient Integrated Water Resources Management","booktitle":"Modelling and Control for Participatory Planning and Managing Water Systems","author":[{"propositions":[],"lastnames":["Castelletti"],"firstnames":["A."],"suffixes":[]},{"propositions":["de"],"lastnames":["Rigo"],"firstnames":["D."],"suffixes":[]},{"propositions":[],"lastnames":["Rizzoli"],"firstnames":["A.","E."],"suffixes":[]},{"propositions":[],"lastnames":["Soncini-Sessa"],"firstnames":["R."],"suffixes":[]},{"propositions":[],"lastnames":["Weber"],"firstnames":["E."],"suffixes":[]}],"editor":[{"propositions":[],"lastnames":["Soncini-Sessa"],"firstnames":["R."],"suffixes":[]}],"date":"2004-09","publisher":"Clup","location":"Italy","url":"http://mfkp.org/INRMM/article/10812626","abstract":"Design of policies within the integrated water resources management (IWRM) paradigm demands to take into account multiple objectives such as flood protection, water supply for hydropower generation, irrigation and urban use, imposition of minimum environmental flows, etc.. Finding efficient water management policies is a demanding task and Stochastic Dynamic Programming (SDP) can provide an effective solution methodology. The efficiency boost is even more pronounced when the scale of integration of the water management problem spans networks of water resources (i.e. sets of interconnected reservoirs, or wide-area water distribution systems). Unfortunately, SDP suffers from the so-called ” curse of dimensionality”, that is, computational times and memory storage requirements increase exponentially with the dimension of the problem (number of reservoirs and water diversions), and rapidly the problem becomes intractable. Neuro-dynamic programming (NDP) can sensibly mitigate both of these problems by approximating the Bell- man functions with Artificial Neural Networks (ANNs). In this paper we present the theoretical framework of this approach and some preliminary results obtained on a real world case study, where the NDP approach to IWRM problems has been applied to a multipurpose water reservoir network.","isbn":"978-88-7090-732-2","keywords":"*imported-from-citeulike-INRMM,~INRMM-MiD:c-10812626,artificial-neural-networks,curse-of-dimensionality,integrated-water-resources-management,neuro-dynamic-programming","options":"useprefix=true","bibtex":"@incollection{castellettiNeuroDynamicProgrammingEfficient2004,\n title = {Neuro-{{Dynamic Programming}} for the Efficient Integrated Water Resources Management},\n booktitle = {Modelling and Control for Participatory Planning and Managing Water Systems},\n author = {Castelletti, A. and de Rigo, D. and Rizzoli, A. E. and Soncini-Sessa, R. and Weber, E.},\n editor = {Soncini-Sessa, R.},\n date = {2004-09},\n publisher = {{Clup}},\n location = {{Italy}},\n url = {http://mfkp.org/INRMM/article/10812626},\n abstract = {Design of policies within the integrated water resources management (IWRM)\n\nparadigm demands to take into account multiple objectives such as flood protection, water\n\nsupply for hydropower generation, irrigation and urban use, imposition of minimum environmental flows, etc.. Finding efficient water management policies is a demanding task\n\nand Stochastic Dynamic Programming (SDP) can provide an effective solution methodology. The efficiency boost is even more pronounced when the scale of integration of the\n\nwater management problem spans networks of water resources (i.e. sets of interconnected\n\nreservoirs, or wide-area water distribution systems). Unfortunately, SDP suffers from the\n\nso-called ” curse of dimensionality”, that is, computational times and memory storage requirements increase exponentially with the dimension of the problem (number of reservoirs\n\nand water diversions), and rapidly the problem becomes intractable. Neuro-dynamic programming (NDP) can sensibly mitigate both of these problems by approximating the Bell-\n\nman functions with Artificial Neural Networks (ANNs). In this paper we present the theoretical framework of this approach and some preliminary results obtained on a real world\n\ncase study, where the NDP approach to IWRM problems has been applied to a multipurpose water reservoir network.},\n isbn = {978-88-7090-732-2},\n keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-10812626,artificial-neural-networks,curse-of-dimensionality,integrated-water-resources-management,neuro-dynamic-programming},\n options = {useprefix=true}\n}\n\n","author_short":["Castelletti, A.","de Rigo, D.","Rizzoli, A. E.","Soncini-Sessa, R.","Weber, E."],"editor_short":["Soncini-Sessa, R."],"key":"castellettiNeuroDynamicProgrammingEfficient2004","id":"castellettiNeuroDynamicProgrammingEfficient2004","bibbaseid":"castelletti-derigo-rizzoli-soncinisessa-weber-neurodynamicprogrammingfortheefficientintegratedwaterresourcesmanagement","role":"author","urls":{"Paper":"http://mfkp.org/INRMM/article/10812626"},"keyword":["*imported-from-citeulike-INRMM","~INRMM-MiD:c-10812626","artificial-neural-networks","curse-of-dimensionality","integrated-water-resources-management","neuro-dynamic-programming"],"downloads":0},"bibtype":"incollection","biburl":"https://tmpfiles.org/dl/58794/INRMM.bib","creationDate":"2020-07-02T22:41:03.913Z","downloads":0,"keywords":["*imported-from-citeulike-inrmm","~inrmm-mid:c-10812626","artificial-neural-networks","curse-of-dimensionality","integrated-water-resources-management","neuro-dynamic-programming"],"search_terms":["neuro","dynamic","programming","efficient","integrated","water","resources","management","castelletti","de rigo","rizzoli","soncini-sessa","weber"],"title":"Neuro-Dynamic Programming for the Efficient Integrated Water Resources Management","year":null,"dataSources":["DXuKbcZTirdigFKPF"]}