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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.
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- ÉditeurBirkhauser Boston Inc
- Date d'édition1994
- ISBN 10 0817637354
- ISBN 13 9780817637354
- ReliureRelié
- Langueanglais
- Nombre de pages422
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Hierarchical Decision Making in Stochastic Manufacturing Systems
Edité par
Birkhauser, 1994
ISBN 10 : 0817637354
ISBN 13 : 9780817637354
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Hierarchical Decision Making in Stochastic Manufacturing Systems
Edité par
Birkhauser, 1994
ISBN 10 : 0817637354
ISBN 13 : 9780817637354
Ancien ou d'occasion
Couverture rigide
Vendeur : ThriftBooks-Atlanta, AUSTELL, GA, Etats-Unis
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Hierarchical Decision Making in Stochastic Manufacturing Systems
Edité par
Birkhäuser, 1994
ISBN 10 : 0817637354
ISBN 13 : 9780817637354
Ancien ou d'occasion
Couverture rigide
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Hierarchical Decision Making in Stochastic Manufacturing Systems
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Hierarchical Decision Making in Stochastic Manufacturing Systems
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Hierarchical Decision Making in Stochastic Manufacturing Systems
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Birkhäuser Boston, 1994
ISBN 10 : 0817637354
ISBN 13 : 9780817637354
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 problem. N° de réf. du vendeur 5975482
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Hierarchical Decision Making in Stochastic Manufacturing Systems
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Birkhäuser Boston, Birkhäuser Boston Dez 1994, 1994
ISBN 10 : 0817637354
ISBN 13 : 9780817637354
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 444 pp. Englisch. N° de réf. du vendeur 9780817637354
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Hierarchical Decision Making in Stochastic Manufacturing Systems
Edité par
Birkhauser Boston Inc, 1994
ISBN 10 : 0817637354
ISBN 13 : 9780817637354
Ancien ou d'occasion
Couverture rigide
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Hardcover. Etat : Bon. Ancien livre de bibliothèque. Légères traces d'usure sur la couverture. Edition 1994. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Slight signs of wear on the cover. Edition 1994. Ammareal gives back up to 15% of this item's net price to charity organizations. N° de réf. du vendeur D-286-799
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Hierarchical Decision Making in Stochastic Manufacturing Systems (Systems & Control: Foundations & Applications)
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Hierarchical Decision Making in Stochastic Manufacturing Systems
Edité par
Birkhäuser Boston, Birkhäuser Boston, 1994
ISBN 10 : 0817637354
ISBN 13 : 9780817637354
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N° de réf. du vendeur 9780817637354
Quantité disponible : 1 disponible(s)