Average—Cost Control of Stochastic Manufacturing Systems [electronic resource] / by Suresh P. Sethi, Hanqin Zhang, Qing Zhang.
Contributor(s): Zhang, Hanqin [author.] | Zhang, Qing [author.] | SpringerLink (Online service)Material type: TextSeries: Stochastic Modelling and Applied Probability: 54Publisher: New York, NY : Springer New York, 2005Description: XVI, 324 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9780387276151Subject(s): Business | Leadership | Production management | Operations research | Decision making | Applied mathematics | Engineering mathematics | System theory | Probabilities | Business and Management | Operations Management | Business Strategy/Leadership | Applications of Mathematics | Systems Theory, Control | Probability Theory and Stochastic Processes | Operation Research/Decision TheoryAdditional physical formats: Printed edition:: No titleDDC classification: 658.5 LOC classification: TS155-TS194Online resources: Click here to access online
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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.
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. .