Data-Driven Optimization and Knowledge Discovery for an Enterprise Information System
Language: English
Published by Springer, 2015
- Hardcover
- Used

Seller: Buchpark, Trebbin, GermanyBuchpark
AbeBooks seller since September 30, 2021
Condition: Used - Fine
US$ 94.98
Quantity: 2 available
Add to basketItem description from seller
Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This book provides a comprehensive set of optimization and prediction techniques for an enterprise information system. Readers with a background in operations research, system engineering, statistics, or data analytics can use this book as a reference to derive insight from data and use this knowledge as guidance for production management. The authors identify the key challenges in enterprise information management and present results that have emerged from leading-edge research in this domain. Coverage includes topics ranging from task scheduling and resource allocation, to workflow optimization, process time and status prediction, order admission policies optimization, and enterprise service-level performance analysis and prediction. With its emphasis on the above topics, this book provides an in-depth look at enterprise information management solutions that are needed for greater automation and reconfigurability-based fault tolerance, as well as to obtain data-driven recommendations for effective decision-making.…
Seller Inventory # 25520049/2
- Title
- Data-Driven Optimization and Knowledge Discovery for an Enterprise Information System
- Author
- Duan, Qing
- Publisher
- Springer
- Publication year
- 2015
- Condition
- Sehr gut
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3319187376
- ISBN 13
- 9783319187372
- Seller catalogs
- Bücher
This book provides a comprehensive set of optimization and prediction techniques for an enterprise information system. Readers with a background in operations research, system engineering, statistics, or data analytics can use this book as a reference to derive insight from data and use this knowledge as guidance for production management. The authors identify the key challenges in enterprise information management and present results that have emerged from leading-edge research in this domain. Coverage includes topics ranging from task scheduling and resource allocation, to workflow optimization, process time and status prediction, order admission policies optimization, and enterprise service-level performance analysis and prediction. With its emphasis on the above topics, this book provides an in-depth look at enterprise information management solutions that are needed for greater automation and reconfigurability-based fault tolerance, as well as to obtain data-driven recommendations for effective decision-making.
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