Author/Authors :
Ruan, Junhu College of Economics and Management - Northwest A&F University, Yangling, China , Wang, Xuping Faculty of Management and Economics - Dalian University of Technology, Dalian, China , Yue, Chengyan Department of Applied Economics - University of Minnesota, Minneapolis, MN, USA , Chen, Guo School of Electrical and Information Engineering - University of Sydney, Sydney, NSW, Australia , Kim, Minsoo Department of Systems Management and Engineering - Pukyong National University, Busan, Republic of Korea
Abstract :
In the literature, lots of optimization models and algorithms have been presented to deal with the operation and control issues in various domains such as intelligent manufacturing, production scheduling, transportation routing, service arrangement, and space exploration. Extant related works have promoted the development of conventional optimization and control theories, and quite a few of them have been widely used in the real world.
With the emergence of recent information technologies including Wireless Sensing Networks, Internet of Things (IOT), Cloud Computing, and Distributed Computing, people can obtain and process far more than what they could, generally within shorter time and with fewer costs. In addition, the application of the information technologies has been bringing about new challenges. One growing challenge is the Big Data problem. Although the Big Data problems and the like may provide chances for people to explore new rules and laws of the universe, they will become catastrophes if not well dealt with.
Thus, people should find new ways and tools in various domains to cope with the emerging challenges. Without exception, extant optimization models and algorithms need to be extended or reformulated for dealing with the reshaped operation and control issues by new information technologies.
