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.
Table des matières
and Models of Manufacturing Systems.- Concept of Near—Optimal Control.- Models of Manufacturing Systems.- Optimal Control of Manufacturing Systems: Existence and Characterization.- Optimal Control of Parallel—Machine Systems.- Optimal Control of Dynamic Flowshops.- Optimal Controls of Dynamic Jobshops.- Risk-Sensitive Control.- Near—Optimal Controls.- Near—Optimal Control of Parallel—Machine Systems.- Near—Optimal Control of Dynamic Flowshops.- Near—Optimal Controls of Dynamic Jobshops.- Near—Optimal Risk—Sensitive Control.- Conclusions.- Further Extensions and Open Research Problems.
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