Hidden Bibliographic Details
| Other authors / contributors: | Gao, Jianjun.
Lambert, James H.
Ng, Chi-Kong.
Wang, Jun.
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| ISBN: | 9783319535180
3319535188
3319535161
9783319535166
3319535161
9783319535166
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| Digital file characteristics: | text file PDF
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| Notes: | 6.2 Optimal ALM Formulation.
Includes bibliographical references and index.
Print version record.
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| Summary: | This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization, control and resilience management that can be applied to further success. In both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. This "big data" provides new opportunities to improve decision making and addresses risk for individuals as well in organizations. While utilizing data smartly can enhance decision making, how to use and incorporate data into the decision making framework remains a challenging topic. Ultimately the chapters in this book present new models and frameworks to help overcome this obstacle. Optimization and Control for Systems in the Big-Data Era: Theory and Applications is divided into five parts. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications. Part III provides novel insights and new findings in the area of financial optimization analysis. The chapters in Part IV deal with operations analysis, covering flow-shop operations and quick response systems. The book concludes with final remarks and a look to the future of big data related optimization and control problems.
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| Other form: | Print version: Choi, Tsan-Ming. Optimization and Control for Systems in the Big-Data Era : Theory and Applications. Cham : Springer International Publishing, ©2017 9783319535166
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| Standard no.: | 10.1007/978-3-319-53518-0
9783319535166
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