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EBOOK
Author Choi, Tsan-Ming.
Title Optimization and Control for Systems in the Big-Data Era : Theory and Applications.
Imprint Cham : Springer International Publishing, 2017.

LOCATION CALL # STATUS MESSAGE
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LOCATION CALL # STATUS MESSAGE
 OHIOLINK SPRINGER EBOOKS    ONLINE  
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Series International Series in Operations Research & Management Science ; v. 252
International series in operations research & management science.
Subject Business.
Operations research.
Decision making.
Mathematical optimization.
Alt Name Gao, Jianjun.
Lambert, James H. (Research professor of systems engineering)
Ng, Chi-Kong.
Wang, Jun (Writer on big data)
Description 1 online resource (281 pages).
Contents Preface; Contents; Contributors; 1 Optimization and Control for Systems in the Big Data Era: An Introduction; 1.1 Optimization and Control in Big Data Era; 1.2 Reviews on Theories; 1.3 Reviews on Applications; 1.4 Financial Optimization Analysis; 1.5 Operations Analysis; References; Part I Reviews on Optimization and Control Theories; 2 Dual Control in Big Data Era: An Overview; 2.1 Introduction; 2.2 Classification of Controllers; 2.2.1 Non-dual Controller; 2.2.1.1 Certainty Equivalence Controller; 2.2.1.2 One-Step Cautious Controller; 2.2.1.3 The Open-Loop Feedback Optimal Controller.
2.2.2 Dual Controller2.2.2.1 Optimal Dual Controller; 2.2.2.2 Suboptimal Dual Controller; 2.2.2.3 Optimal Nominal Dual Controller; 2.3 An Example: LQG Problems with Unknown Parameters; 2.3.1 Optimal Dual Control; 2.3.2 Open-Loop Feedback Control; 2.3.3 Active Open-Loop Feedback Control: Variance Minimization Approach; 2.3.4 Optimal Nominal Dual Control; 2.4 Dual Control in Big Data Era; 2.4.1 Economic Systems; 2.4.2 Manufacturing Processes; 2.4.3 Automobile Systems; 2.4.4 Robotics; 2.4.5 Information Retrieval; 2.5 Conclusions; References.
3 Time Inconsistency and Self-Control Optimization Problems: Progress and Challenges3.1 Introduction; 3.2 Progress; 3.2.1 Separable Problem Versus Non-separable Problem; 3.2.2 Approaches Dealing with Time Inconsistency; 3.3 Challenges; 3.3.1 Dynamic Mean-Risk Portfolio Optimization Problems; 3.3.2 Time Inconsistency Generated by Probability Weighting; 3.3.3 Data Challenge; References; 4 Quadratic Convex Reformulations for Integer and Mixed-Integer Quadratic Programs; 4.1 Introduction; 4.2 QCR for Binary Quadratic Programming; 4.2.1 QCR with No Additional Variables.
4.2.2 QCR with Additional Variables4.3 QCR for Linear Equality Constrained Binary Quadratic Programming; 4.4 Generalization of QCR to MIQCQP; 4.4.1 QCR for Binary Quadratically Constrained Quadratic Programming; 4.4.2 QCR for Mixed-Binary Quadratic Programming; 4.4.3 QCR for MIQCQP; 4.4.4 Compact QCR for MIQCQP; 4.4.5 With or Without Additional Variables; 4.5 QCR for Semi-Continuous Quadratic Programming; 4.6 Concluding Remark; References; Part II Reviews on Optimization and Control Applications; 5 Measurements of Financial Contagion: A Primary Review from the Perspective of Structural Break.
5.1 Introduction5.2 Concepts of Financial Contagion; 5.3 Contagion of Financial Markets; 5.3.1 Volatility Analysis; 5.3.2 Correlation Analysis; 5.3.3 Factor Model Based Approaches; 5.3.3.1 Contagion of Individual Shocks; 5.3.3.2 Contagion of Common Shocks and Transmission Channels; 5.4 Contagion of Interbank System; 5.4.1 Network Model of Interbank Contagion; 5.4.2 Contagion via Portfolio Overlapping; 5.5 Potential Applications of Big Data to Financial Contagion; References; 6 Asset-Liability Management in Continuous-Time: Cointegration and Exponential Utility; 6.1 Introduction.
Note 6.2 Optimal ALM Formulation.
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.
Bibliography Note Includes bibliographical references and index.
Note Print version record.
ISBN 9783319535180
3319535188
3319535161
9783319535166
3319535161
9783319535166
ISBN/ISSN 10.1007/978-3-319-53518-0
9783319535166
OCLC # 987102811
Additional Format Print version: Choi, Tsan-Ming. Optimization and Control for Systems in the Big-Data Era : Theory and Applications. Cham : Springer International Publishing, 2017 9783319535166