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.
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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.
Imprint | Springer-Verlag New York |
Country of origin | United States |
Series | Stochastic Modelling and Applied Probability, 54 |
Release date | November 2010 |
Availability | Expected to ship within 10 - 15 working days |
First published | 2005 |
Authors | Suresh P. Sethi, Han-Qin Zhang, Qing Zhang |
Dimensions | 235 x 155 x 18mm (L x W x T) |
Format | Paperback |
Pages | 324 |
Edition | Softcover reprint of hardcover 1st ed. 2005 |
ISBN-13 | 978-1-4419-1954-0 |
Barcode | 9781441919540 |
Categories | |
LSN | 1-4419-1954-6 |