Springer Average-Cost Control of Stochastic Manufacturing Systems: 54 (Stochastic Modelling and Applied Probability, 54)

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. Review From the reviews of the first edition: "This book is a study on the optimal control of manufacturing systems subject to breakdowns and repairs. … Six appendices provide mathematical technical support. 153 references are given. There is an author index as well as a subject index. This book is a useful reference on the stochastic optimal control of manufacturing systems and is recommended." (A. Akutowicz, Zentralblatt MATH, Vol. 1078, 2006) "The book under review is concerned with systems that consist of machines subjects to breakdown and repair … . The book is written for applied mathematics, operations researchers, as well as practitioners working in manufacturing. In summary, this is an excellent book devoted to a fast growing area, which has significant impact on the economy. It is conceivable that … this book will further stimulate subsequent research in production planning as well as in systems theory and stochastic control." (George Yin, Mathematical Reviews, Issue 2005 k) 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.