Complex & Intelligent Systems - Call for Papers: Complex & Intelligent Systems
Special Issue on "Knowledge Fusion Intelligent Optimization for Complex Systems"
Theme:
Due to various complexities in real-world industry and service systems, many optimization problems cannot be solved effectively by traditional methods. Intelligent optimization including evolutionary computation and swarm intelligence has been successfully applied to complex systems in a variety of engineering fields. To enhance the optimization capability when solving particular problems, it is very important to incorporate knowledge in the intelligent algorithms. Knowledge fusion intelligent optimization is concerned with the use of the problem specific properties and the prior information for the strategy design in the framework of intelligent optimization. The key issues of knowledge fusion optmization include knowledge representation, knowledge utilization, model management, strategy design, learning mechanism, and the related control scheme. During the past few years, increasing attention has been paid to the theoretical analysis, algorithm design, and performance improvement of the knowledge fusion optimization as well as a wide range of applications in complex engineering systems. This special issue intends to give the state-of-the-art of the knowledge fusion intelligent optimization for complex systems. It aims to provide a platform for researchers to share innovative work in such an emerging area. Interdisciplinary methodologies may be given based on the innovative intelligent optimization and knowledge engineering for complex systems.
Scope of Topics:
The aim of this special issue is to reflect the most recent developments of knowledge fusion intelligent optimization for complex systems. The topics include, but are not limited to:
- Knowledge representation and knowledge utilization in intelligent optimization
- Reinforcement learning based intelligent algorithms for complex systems
- Theoretical analysis knowledge fusion intelligent optimization
- Knowledge fusion intelligent algorithms for multi-objective optimization problems
- Knowledge fusion intelligent algorithms for uncertain optimization problems
- Knowledge fusion intelligent algorithms for simulation optimization problems
- Applications of knowledge fusion intelligent optimization in industry and service systems
- Survey of knowledge fusion intelligent optimization
Important Dates:
Manuscript submission: June 30, 2020
First review completed: August 31, 2020
Final review completed: November 30, 2020
Acceptance notification: December 31, 2020
Anticipated publication: June 2021
Submissions:
All manuscripts and any supplementary materials should be submitted via the CAIS submission web site at https://www.editorialmanager.com/cais/default.aspx (this opens in a new tab)
Guest Editors:
Professor Ling Wang, Department of Automation, Tsinghua University, Beijing, China
Email: wangling@tsinghua.edu.cn (this opens in a new tab)
Associate Professor Feng Wang, School of Computer, Wuhan University, Wuhan, China
Email: fengwang@whu.edu.cn
Bios of Guest Editors:
Ling Wang received the B.S. degree in automation and the Ph.D. degree in Control Theory and Control Engineering from Tsinghua University, Beijing, China, in 1995 and 1999, respectively. Since 1999, he has been with the Department of Automation, Tsinghua University, where he became a Full Professor in 2008. He has authored 5 academic books and over 170 SCI-indexed papers. His current research interests include intelligent optimization and production scheduling.
Prof. Wang was a recipient of the National Natural Science Fund for Distinguished Young Scholars of China, the National Natural Science Award (Second Place) in 2014, the Science and Technology Award of Beijing City in 2008, and the Natural Science Award (First Place in 2003 and Second Place in 2007) nominated by the Ministry of Education of China. He is currently the Editor-in-Chief of the International Journal of Automation and Control (IJAAC), and an Associate Editor of the IEEE Transactions on Evolutionary Computation and Swarm & Evolutionary Computation. He acted as the Guest Editor of many journals including Memetic Computing, Computers & Industrial Engineering, Neurocomputing, and Journal of Intelligent Manufacturing.
Feng Wang received the M.S. and Ph.D. degrees in Computer Science in 2005 and 2008, respectively from Wuhan University, China. Since 2008, she has been with State Key Lab of Software Engineering of Wuhan University. She is currently an associate professor with School of Computer Science, Wuhan University. Her research interests include evolutionary computation, intelligent information retrieval, and machine learning.
Dr. Wang is currently an Associate Editor of the International Journal of Cognitive Informatics and Natural Intelligence (IJCINI). She acted as the Guest Editor of Information Sciences.