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Data-driven optimization and knowled...

Chakrabarty, Krishnendu.

Data-driven optimization and knowledge discovery for an enterprise information system

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data-driven optimization and knowledge discovery for an enterprise information systemby Qing Duan, Krishnendu Chakrabarty, Jun Zeng.
作者:	Duan, Qing.
其他作者:	Chakrabarty, Krishnendu.
出版者:	Cham :Springer International Publishing :2015.
面頁冊數:	xii, 160 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Management information systems.
電子資源:	http://dx.doi.org/10.1007/978-3-319-18738-9
ISBN:	9783319187389 (electronic bk.)

Data-driven optimization and knowledge discovery for an enterprise information system
Duan, Qing.

Data-driven optimization and knowledge discovery for an enterprise information system[electronic resource] /by Qing Duan, Krishnendu Chakrabarty, Jun Zeng. - Cham :Springer International Publishing :2015. - xii, 160 p. :ill. (some col.), digital ;24 cm.

Introduction -- Production Simulation Platform -- Production Workflow Optimizations -- Predictions of Process-Execution Time and Process-Execution Status -- Optimization of Order-Admission Policies -- Conclusion.

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.

ISBN: 9783319187389 (electronic bk.)

Standard No.: 10.1007/978-3-319-18738-9doiSubjects--Topical Terms:

199355
Management information systems.

LC Class. No.: T58.6

Dewey Class. No.: 658.4038011

Data-driven optimization and knowledge discovery for an enterprise information system
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520 $a 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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