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

Apoio

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
Métodos de Pagamento

Tabela de Conteúdo

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

Sobre o autor

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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Língua Inglês ● Formato PDF ● Páginas 160 ● ISBN 9783319187389 ● Tamanho do arquivo 4.9 MB ● Editora Springer International Publishing ● Cidade Cham ● País CH ● Publicado 2015 ● Carregável 24 meses ● Moeda EUR ● ID 4334286 ● Proteção contra cópia DRM social

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