Vijay Gadepally; Timothy Mattson; Michael Stonebraker; Tim Kraska; Fusheng Wang; Gang Luo; Jun Kong; Alevti Dubovitskaya Springer Nature Switzerland AG (2021) Pehmeäkantinen kirja
El Kindi Rezig; Vijay Gadepally; Timothy Mattson; Michael Stonebraker; Tim Kraska; Fusheng Wang; Gang Luo; Jun Kong; Dub Springer Nature Switzerland AG (2021) Pehmeäkantinen kirja
El Kindi Rezig; Vijay Gadepally; Timothy Mattson; Michael Stonebraker; Tim Kraska; Jun Kong; Gang Luo; Dejun Teng; Wang Springer International Publishing AG (2023) Pehmeäkantinen kirja
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.
