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Other titles in the CRC Monographs and Surveys in Pure and Applied Mathematics series:

CRC Monographs and Surveys in Pure and Applied Mathematics #110: Iterative Dynamic Programming

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CRC Monographs and Surveys in Pure and Applied Mathematics #110: Iterative Dynamic Programming Cover

 

Synopses & Reviews

Publisher Comments:

With iteration, dynamic programming becomes an effective optimization procedure for very high-dimensional optimal control problems and has demonstrated applicability to singular control problems. Recently, iterative dynamic programming (IDP) has been refined to handle inequality state constraints and noncontinuous functions. This book offers the first comprehensive presentation of this powerful tool. It brings together the results of work carried out by the author and others along with the insight that led to its development. The author provides the necessary background, examines the effects of the parameters involved, and clearly illustrates IDP's advantages.

Book News Annotation:

Brings together results of work carried out by the author and others, previously available only in scattered journal articles, along with insights that led to the development of iterative dynamic programming (IDP). Provides necessary background, then examines the effects of the parameters involved and illustrates IDP's advantages. Contains chapters on allowable values for control, piecewise linear control, time-delay systems, and state constraints. Appendices offer computer code. Of interest to applied mathematicians and theoretical physicists, as well as computer science engineers. Luus is professor of chemical engineering at the University of Toronto, Canada.
Annotation c. Book News, Inc., Portland, OR (booknews.com)

Synopsis:

Dynamic programming is a powerful method for solving optimization problems, but has a number of drawbacks that limit its use to solving problems of very low dimension. To overcome these limitations, author Rein Luus suggested using it in an iterative fashion. Although this method required vast computer resources, modifications to his original scheme have made the computational procedure feasible.

With iteration, dynamic programming becomes an effective optimization procedure for very high-dimensional optimal control problems and has demonstrated applicability to singular control problems. Recently, iterative dynamic programming (IDP) has been refined to handle inequality state constraints and noncontinuous functions.

Iterative Dynamic Programming offers a comprehensive presentation of this powerful tool. It brings together the results of work carried out by the author and others - previously available only in scattered journal articles - along with the insight that led to its development. The author provides the necessary background, examines the effects of the parameters involved, and clearly illustrates IDP's advantages.

Product Details

ISBN:
9781584881483
Author:
Luus, Rein
Publisher:
CRC Press
Author:
Luus, Ryan
Location:
Boca Raton, Fla.
Subject:
General
Subject:
Linear Programming
Subject:
Programming - General
Subject:
Iterative methods (Mathematics)
Subject:
Dynamic programming
Subject:
Iterative methods.
Subject:
Mathematics-Computer
Edition Description:
Paperback
Series:
CRC Monographs and Surveys in Pure and Applied Mathematics (Paperback)
Series Volume:
110
Publication Date:
20000131
Binding:
Paperback
Language:
English
Illustrations:
Yes
Pages:
324
Dimensions:
9.50x6.42x.93 in. 1.43 lbs.

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CRC Monographs and Surveys in Pure and Applied Mathematics #110: Iterative Dynamic Programming New Hardcover
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Product details 324 pages Chapman & Hall/CRC - English 9781584881483 Reviews:
"Synopsis" by , Dynamic programming is a powerful method for solving optimization problems, but has a number of drawbacks that limit its use to solving problems of very low dimension. To overcome these limitations, author Rein Luus suggested using it in an iterative fashion. Although this method required vast computer resources, modifications to his original scheme have made the computational procedure feasible.

With iteration, dynamic programming becomes an effective optimization procedure for very high-dimensional optimal control problems and has demonstrated applicability to singular control problems. Recently, iterative dynamic programming (IDP) has been refined to handle inequality state constraints and noncontinuous functions.

Iterative Dynamic Programming offers a comprehensive presentation of this powerful tool. It brings together the results of work carried out by the author and others - previously available only in scattered journal articles - along with the insight that led to its development. The author provides the necessary background, examines the effects of the parameters involved, and clearly illustrates IDP's advantages.

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