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duan qing; chakrabarty krishnendu; zeng jun - data-driven optimization and knowledge discovery for an enterprise information system

Data-Driven Optimization and Knowledge Discovery for an Enterprise Information System

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Dettagli

Genere:Libro
Lingua: Inglese
Editore:

Springer

Pubblicazione: 06/2015
Edizione: 2015





Trama

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 reconfigurabilty-based fault tolerance, as well as to obtain data-driven recommendations for effective decision-making.





Sommario

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




Autore

Qing Duan is a data scientist at Paypal, Inc. Krishnendu Chakrabarty is a Professor in the Department of Electrical and Computer Engineering at Duke University. Jun Zeng is a principal researcher at Hewlett-Packard Labs.










Altre Informazioni

ISBN:

9783319187372

Condizione: Nuovo
Dimensioni: 235 x 155 mm Ø 482 gr
Formato: Copertina rigida
Illustration Notes:XII, 160 p. 76 illus., 47 illus. in color.
Pagine Arabe: 160
Pagine Romane: xii


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