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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Suresh P. Sethi is the Eugene McDermott Chair Professor of Operations Management and Director of the Center for Intelligent Supply Networks (C4ISN) at the University of Texas at Dallas, USA. He has made significant contributions in the fields of manufacturing and operations management, finance and economics, marketing, industrial engineering, operations research, and optimal control. He is best known for his textbook on optimal control, developments of the Sethi advertising model and Sethi-Skiba points, pioneering works on stochastic inventory models especially with incomplete information, and seminal papers on consumption-investment problems with bankruptcy. He has received numerous prestigious honors and awards such as IEEE Fellow, INFORMS Fellow, SIAM Fellow, POMS Fellow, AAAS Fellow, IITB Distinguished Alum, Tepper School of Business-Alumni Achievement Award, and POMS President (2012). Two conferences have been organized in his honor: in Aix en Provence in 2005 and at the UT Dallas in 2006 with Harry M. Markowitz, a 1990 Nobel Laureate in Economics, as the keynote speaker. Also, two books have been edited in his honor. His past and present editorial positions include Departmental Editor of Production and Operations Management, Corresponding Editor of SIAM Journal on Control and Optimization, and Associate Editor of Operations Research, M&SOM, and Automatica.
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.
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Taschenbuch. Zustand: Neu. Average-Cost Control of Stochastic Manufacturing Systems | Suresh P. Sethi (u. a.) | Taschenbuch | Stochastic Modelling and Applied Probability | xvi | Englisch | 2010 | Springer | EAN 9781441919540 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Artikel-Nr. 107253268
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Artikel-Nr. 9781441919540
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