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dc.contributor.authorSniedovich, Moshe
dc.date.accessioned2016-09-13T22:02:57Z
dc.date.available2016-09-13T22:02:57Z
dc.date.issued1976-12
dc.identifier.urihttp://hdl.handle.net/10150/620117
dc.description.abstractThis dissertation contains a discussion concerning the validity of the principle of optimality and the dynamic programming algorithm in the context of discrete time and state multistage decision processes. The multistage decision model developed for the purpose of the investigation is of a general structure, especially as far as the reward function is concerned. The validity of the dynamic programming algorithm as a solution method is investigated and results are obtained for a rather wide class of decision processes. The intimate relationship between the principle and the algorithm is investigated and certain important conclusions are derived. In addition to the theoretical considerations involved in the implementation of the dynamic programming algorithm, some modeling and computational aspects are also investigated. It is demonstrated that the multistage decision model and the dynamic programming algorithm as defined in this study provide a solid framework for handling a wide class of multistage decision processes. The flexibility of the dynamic programming algorithm as a solution procedure for nonroutine reservoir control problems is demonstrated by two examples, one of which is a reliability problem. To the best of the author's knowledge, many of the theoretical derivations presented in this study, especially those concerning the relation between the principle of optimality and the dynamic programming algorithm, are novel.
dc.description.sponsorshipThe research effort was supported in part by funds provided by the National Science Foundation through a grant (GK- 35915) on "Space Time Sampling and Equations of Hydrologic Systems" and in part by funds provided by the Office of Water Resources Research through a grant (14-31-0001-5056) on "Practical Use of Decision Theory to Assess Uncertainties about Actions Affecting the Environment."en
dc.language.isoen_USen
dc.publisherDepartment of Hydrology and Water Resources, University of Arizona (Tucson, AZ)en
dc.relation.ispartofseriesTechnical Reports on Hydrology and Water Resources, No. 27en
dc.rightsCopyright © Arizona Board of Regentsen
dc.sourceProvided by the Department of Hydrology and Water Resources.en
dc.subjectDynamic programmingen
dc.subjectDecision making -- Mathematical models.en
dc.subjectMathematical optimization.en
dc.subjectReservoirs -- Mathematical models.en
dc.titleON THE THEORY AND MODELING OF DYNAMIC PROGRAMMING WITH APPLICATIONS IN RESERVOIR OPERATIONen_US
dc.typetexten
dc.typeTechnical Reporten
dc.contributor.departmentDepartment of Hydrology & Water Resources, The University of Arizonaen
dc.description.collectioninformationThis title from the Hydrology & Water Resources Technical Reports collection is made available by the Department of Hydrology & Atmospheric Sciences and the University Libraries, University of Arizona. If you have questions about titles in this collection, please contact repository@u.library.arizona.edu.en
refterms.dateFOA2018-09-11T14:46:40Z
html.description.abstractThis dissertation contains a discussion concerning the validity of the principle of optimality and the dynamic programming algorithm in the context of discrete time and state multistage decision processes. The multistage decision model developed for the purpose of the investigation is of a general structure, especially as far as the reward function is concerned. The validity of the dynamic programming algorithm as a solution method is investigated and results are obtained for a rather wide class of decision processes. The intimate relationship between the principle and the algorithm is investigated and certain important conclusions are derived. In addition to the theoretical considerations involved in the implementation of the dynamic programming algorithm, some modeling and computational aspects are also investigated. It is demonstrated that the multistage decision model and the dynamic programming algorithm as defined in this study provide a solid framework for handling a wide class of multistage decision processes. The flexibility of the dynamic programming algorithm as a solution procedure for nonroutine reservoir control problems is demonstrated by two examples, one of which is a reliability problem. To the best of the author's knowledge, many of the theoretical derivations presented in this study, especially those concerning the relation between the principle of optimality and the dynamic programming algorithm, are novel.


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