DYNAMIC STOCHASTIC OPTIMIZATION by Kurt Marti (Editor), Yuri Ermoliev (Editor), Georg Ch. Pflug (Editor) ( 9783540405061 )

Item Details

Title:

DYNAMIC STOCHASTIC OPTIMIZATION

By:

Kurt Marti (Editor), Yuri Ermoliev (Editor), Georg Ch. Pflug (Editor)

Format:

Paperback

List price:	£109.99
We currently do not stock this item, please contact the publisher directly for further information.

ISBN 10:

3540405062

ISBN 13:

9783540405061

Publisher:

SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG

Pub. date:

29 October, 2003

Edition:

Softcover reprint of the original 1st ed. 2004

Series:

Lecture Notes in Economics and Mathematical Systems 532

Pages:

336

Synopsis:

Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic- itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec- tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci- sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu- tions. Objective and constraint functions of dynamic stochastic optimization problems have the form of multidimensional integrals of rather involved in- that may have a nonsmooth and even discontinuous character - the tegrands typical situation for "hit-or-miss" type of decision making problems involving irreversibility ofdecisions or/and abrupt changes ofthe system. In general, the exact evaluation of such functions (as is assumed in the standard optimization and control theory) is practically impossible. Also, the problem does not often possess the separability properties that allow to derive the standard in control theory recursive (Bellman) equations.

Illustrations:

31 Tables, black and white; VIII, 336 p.

Publication:

Germany

Imprint:

Springer-Verlag Berlin and Heidelberg GmbH & Co. K

Returns:

Returnable

Some other items by this author:

COPING WITH UNCERTAINTY (PB)

DESCENT DIRECTIONS AND EFFICIENT SOLUTIONS IN DISCRETELY DISTRIBUTED STOCHASTIC PROGRAMS (PB)

EINFUHRUNG IN DIE LINEARE UND NICHTLINEARE OPTIMIERUNG (PB)