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.
Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/620117 |
Date | 12 1900 |
Creators | Sniedovich, Moshe |
Contributors | Department of Hydrology & Water Resources, The University of Arizona |
Publisher | Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ) |
Source Sets | University of Arizona |
Language | en_US |
Detected Language | English |
Type | text, Technical Report |
Source | Provided by the Department of Hydrology and Water Resources. |
Rights | Copyright © Arizona Board of Regents |
Relation | Technical Reports on Hydrology and Water Resources, No. 27 |
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