Qing Duan & Krishnendu Chakrabarty 
Data-Driven Optimization and Knowledge Discovery for an Enterprise Information System [PDF ebook] 

Ondersteuning

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.

€88.80
Betalingsmethoden

Inhoudsopgave

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

Over de auteur

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.

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Taal Engels ● Formaat PDF ● Pagina’s 160 ● ISBN 9783319187389 ● Bestandsgrootte 4.9 MB ● Uitgeverij Springer International Publishing ● Stad Cham ● Land CH ● Gepubliceerd 2015 ● Downloadbare 24 maanden ● Valuta EUR ● ID 4334286 ● Kopieerbeveiliging Sociale DRM

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