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Optimization and Control for Systems in the Big-Data Era

Theory and Applications

  • Tsan-Ming Choi
  • Jianjun Gao
  • James H. Lambert
  • Chi-Kong Ng
  • Jun Wang

Part of the International Series in Operations Research & Management Science book series (ISOR, volume 252)

Table of contents

  1. Front Matter
    Pages i-x
  2. Tsan-Ming Choi, Jianjun Gao, James H. Lambert, Chi-Kong Ng, Jun Wang
    Pages 1-6
  3. Reviews on Optimization and Control Theories

  4. Reviews on Optimization and Control Applications

  5. Financial Optimization Analysis

  6. Operations Analysis

    1. Front Matter
      Pages 243-243
    2. Jun Wang, Xiaoxia Zhuang, Baiyi Wu
      Pages 245-251
  7. Concluding Remarks

    1. Front Matter
      Pages 269-269
    2. Tsan-Ming Choi, Jianjun Gao, James H. Lambert, Chi-Kong Ng, Jun Wang
      Pages 271-276
  8. Back Matter
    Pages 277-280

About this book

Introduction

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.

Keywords

Big Data Data-Driven Optimal Control Applications Optimal Control Optimization Risk Analysis Systems Engineering Systems Reliability Systems Resilience

Editors and affiliations

  • Tsan-Ming Choi
    • 1
  • Jianjun Gao
    • 2
  • James H. Lambert
    • 3
  • Chi-Kong Ng
    • 4
  • Jun Wang
    • 5
  1. 1.Institute of Textiles and ClothingThe Hong Kong Polytechnic UniversityHung Hom, KowloonHong Kong
  2. 2.School of Information Management and EngineeringShanghai University of Finance and EconomicsShanghaiChina
  3. 3.Department of Systems and Information EngineeringUniversity of VirginiaCharlottesvilleUSA
  4. 4.Department of Systems Engineering and Engineering ManagementThe Chinese University of Hong KongShatin, N.T.Hong Kong
  5. 5.Department of Management Science and Engineering, Business SchoolQingdao UniversityShandongChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-53518-0
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Business and Management
  • Print ISBN 978-3-319-53516-6
  • Online ISBN 978-3-319-53518-0
  • Series Print ISSN 0884-8289
  • Series Online ISSN 2214-7934
  • Buy this book on publisher's site