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.

Zusammenfassung

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.

Inhalt
and Models of Manufacturing Systems.- Concept of NearOptimal Control.- Models of Manufacturing Systems.- Optimal Control of Manufacturing Systems: Existence and Characterization.- Optimal Control of ParallelMachine Systems.- Optimal Control of Dynamic Flowshops.- Optimal Controls of Dynamic Jobshops.- Risk-Sensitive Control.- NearOptimal Controls.- NearOptimal Control of ParallelMachine Systems.- NearOptimal Control of Dynamic Flowshops.- NearOptimal Controls of Dynamic Jobshops.- NearOptimal RiskSensitive Control.- Conclusions.- Further Extensions and Open Research Problems.