Choi T.-M., Gao J., Lambert J.H., Ng C.-K., Wang J. (Eds.) Optimization and Control for Systems in the Big-Data Era: Theory and Applications

Springer International Publishing AG, 2017. — 281 p. — (International Series in Operations Research & Management Science 252) — ISBN: 3319535161.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.Optimization and Control for Systems in the Big Data Era: An Introduction
Dual Control in Big Data Era: An Overview
Time Inconsistency and Self-Control Optimization Problems: Progress and Challenges
Quadratic Convex Reformulations for Integer and Mixed-Integer Quadratic Programs
Measurements of Financial Contagion: A Primary Review from the Perspective of Structural Break
Asset-Liability Management in Continuous-Time: Cointegration and Exponential Utility
A Review of Modern Cryptography: From the World War II Era to the Big-Data Era
Modeling Supply Risk in the New Business Era: Supply Chain Competition and Cooperation
A Parameterized Method for Optimal Multi-Period Mean-Variance Portfolio Selection with Liability
Sparse and Multiple Risk Measures Approach for Data Driven Mean-CVaR Portfolio Optimization Model
Multistage Optioned Portfolio Selection: Mean-Variance Model and Target Tracking Model
Multi-Period Portfolio Selection with Stochastic Investment Horizon
A New Model and Method for Order Selection Problems in Flow-Shop Production
Quick Response Fashion Supply Chains in the Big Data Era
Optimization and Control for Systems in the Big Data Era: Concluding Remarks