Average-Cost Control of Stochastic Manufacturing Systems

Suresh P. Sethi

ISBN 10: 1441919546 / ISBN 13: 9781441919540

Published by Springer New York, Springer New York Nov 2010, 2010

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 340 pp. Englisch.

Seller Inventory # 9781441919540

Bibliographic Details

• Title: Average-Cost Control of Stochastic Manufacturing Systems
• Publisher: Springer New York, Springer New York Nov 2010
• Publication Date: 2010
• Language: English
• ISBN 10: 1441919546
• ISBN 13: 9781441919540
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

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.

From the Back Cover

This book is concerned with hierarchical control of manufacturing systems under uncertainty.  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.  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.  The approach in the book considers manufacturing systems in which events occur at different time scales.