Details

Average-Cost Control of Stochastic Manufacturing Systems

Average-Cost Control of Stochastic Manufacturing Systems


Stochastic Modelling and Applied Probability, Band 54

von: Suresh P. Sethi, Han-Qin Zhang, Qing Zhang

CHF 118.00

Verlag: Springer
Format: PDF
Veröffentl.: 22.03.2006
ISBN/EAN: 9780387276151
Sprache: englisch
Anzahl Seiten: 324

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Beschreibungen

Titelbeschreibung

<P>Most manufacturing systems are large, complex, and operate in an environment of uncertainty. It is common practice to manage such systems in a hierarchical fashion. This book articulates a new theory that shows that hierarchical decision making can in fact lead to a near optimization of system goals. The material in the book cuts across disciplines. It will appeal to graduate students and researchers in applied mathematics, operations management, operations research, and system and control theory.</P>

Inhaltsverzeichnis

and Models of Manufacturing Systems.- Concept of Near—Optimal Control.- Models of Manufacturing Systems.- Optimal Control of Manufacturing Systems: Existence and Characterization.- Optimal Control of Parallel—Machine Systems.- Optimal Control of Dynamic Flowshops.- Optimal Controls of Dynamic Jobshops.- Risk-Sensitive Control.- Near—Optimal Controls.- Near—Optimal Control of Parallel—Machine Systems.- Near—Optimal Control of Dynamic Flowshops.- Near—Optimal Controls of Dynamic Jobshops.- Near—Optimal Risk—Sensitive Control.- Conclusions.- Further Extensions and Open Research Problems.

Back cover copy

<P>This book is concerned with hierarchical control of manufacturing systems under uncertainty.&nbsp; It focuses on system performance measured in long-run average cost criteria, exploring the relationship between control problems with a discounted cost and that with a long-run average cost in connection with hierarchical control.&nbsp; A new theory is articulated that shows that hierarchical decision making in the context of a goal-seeking manufacturing system can lead to a near optimization of its objective.&nbsp; The approach in the book considers manufacturing systems in which events occur at different time scales.&nbsp; </P>

Verkaufsargumente

This book articulates a new theory that shows that hierarchical
decision making in manufacturing systems can lead to a near
optimization of system goals.
It will appeal to graduate students and researchers in applied
mathematics, operations management, operations research, and systems
and control theory.

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