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

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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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Detail Information

Series Title

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Call Number

338.7

Publisher

Cham : Springer., 2015

Collation

xii, 160 pages

Language

English

ISBN/ISSN

9783319187389

Classification

338.7

Content Type

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Media Type

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Carrier Type

online resource

Edition

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Subject(s)

BUSINESS & ECONOMICS Management

Specific Detail Info

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Statement of Responsibility

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Other Information

Cataloger

Kurnadi

Source

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Validator

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Journal Volume

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Journal Issue

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