ON THE THEORY AND MODELING OF DYNAMIC PROGRAMMING WITH APPLICATIONS IN RESERVOIR OPERATION
| dc.contributor.author | Sniedovich, Moshe | * |
| dc.date.accessioned | 2016-09-13T22:02:57Z | |
| dc.date.available | 2016-09-13T22:02:57Z | |
| dc.date.issued | 1976-12 | |
| dc.identifier.uri | http://hdl.handle.net/10150/620117 | |
| dc.description.abstract | This 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.sponsorship | The 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.iso | en_US | en |
| dc.publisher | Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ) | en |
| dc.relation.ispartofseries | Technical Reports on Hydrology and Water Resources, No. 27 | en |
| dc.rights | Copyright © Arizona Board of Regents | en |
| dc.source | Provided by the Department of Hydrology and Water Resources. | en |
| dc.subject | Dynamic programming | en |
| dc.subject | Decision making -- Mathematical models. | en |
| dc.subject | Mathematical optimization. | en |
| dc.subject | Reservoirs -- Mathematical models. | en |
| dc.title | ON THE THEORY AND MODELING OF DYNAMIC PROGRAMMING WITH APPLICATIONS IN RESERVOIR OPERATION | en_US |
| dc.type | text | en |
| dc.type | Technical Report | en |
| dc.contributor.department | Department of Hydrology & Water Resources, The University of Arizona | en |
| dc.description.collectioninformation | This 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.dateFOA | 2018-09-11T14:46:40Z | |
| html.description.abstract | This 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. |
