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Item Details
Title: HIERARCHICAL DECISION MAKING IN STOCHASTIC MANUFACTURING SYSTEMS
By: Suresh P. Sethi, Qing Zhang, A. Kostant (Editor)
Format: Hardback

List price: £119.99


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ISBN 10: 0817637354
ISBN 13: 9780817637354
Publisher: BIRKHAUSER BOSTON INC
Pub. date: 20 December, 1994
Edition: 1994 ed.
Series: Systems & Control: Foundations & Applications
Pages: 422
Description: This text presents an approach to manufacturing systems that is grounded in ideas from economics and control theory. It cuts across the disciplines of operations management, operations research, system and control theory, industrial engineering, probability and statistics and applied maths.
Synopsis: One of the most important methods in dealing with the optimization of large, complex systems is that of hierarchical decomposition. The idea is to reduce the overall complex problem into manageable approximate problems or subproblems, to solve these problems, and to construct a solution of the original problem from the solutions of these simpler prob- lems. Development of such approaches for large complex systems has been identified as a particularly fruitful area by the Committee on the Next Decade in Operations Research (1988) [42] as well as by the Panel on Future Directions in Control Theory (1988) [65]. Most manufacturing firms are complex systems characterized by sev- eral decision subsystems, such as finance, personnel, marketing, and op- erations. They may have several plants and warehouses and a wide variety of machines and equipment devoted to producing a large number of different products. Moreover, they are subject to deterministic as well as stochastic discrete events, such as purchasing new equipment, hiring and layoff of personnel, and machine setups, failures, and repairs.
Illustrations: XVI, 422 p.
Publication: US
Imprint: Birkhauser Boston Inc
Returns: Returnable
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