Prof. Wei-Neng Chen, South China University of Technology
Scalable Parallel and Distributed Swarm Intelligence Algorithms for Large-scale Optimization
Large-scale high-dimensional optimization problems pose two challenges to swarm intelligence (SI) and evolutionary computation (EC) methods. On the one hand, due to the exponential growth of the search space, the number of local optima increases rapidly, and it weakens the effectiveness of EC algorithms. On the other hand, as the computational cost of fitness evaluation increases, and that a larger population size or more generations are also required, the computational time of EC algorithms significantly increases, which weakens their efficiency.
In this report, we will introduce a variety of large-scale EC/SI algorithms. For non-separable problems, the ideas of level-based learning particle swarm optimizer and segmented predominant learning particle swarm optimizer will be presented. For partially separable or graph-based optimization problems, a co-evolution method based on network partitioning will be presented. Furthermore, under parallel and distributed computing environment, the scalability of SI algorithms will be discussed. A co-evolution algorithm with adaptive resource allocation based on the pool model is further developed to improve efficiency and scalability. Finally, I will introduce some applications of large-scale swarm intelligence optimization methods.
Dr. Wei-Neng Chen received the Bachelor’s and Ph.D. degrees in computer science from Sun Yat-sen University, Guangzhou, China, in 2006 and 2012, respectively. Since 2016, he has been a Full Professor with the School of Computer Science and Engineering, South China University of Technology, Guangzhou, where he is also the vice dean of the school. He has co-authored over 100 international journal and conference papers, including more than 40 papers published in the IEEE Transactions journals. His current research interests include computational intelligence, swarm intelligence, network science and their applications.
Dr. Chen was a recipient of the IEEE Computational Intelligence Society (CIS) Outstanding Dissertation Award in 2016, and the National Science Fund for Excellent Young Scholars, China in 2016. He is currently the Vice-Chair of the IEEE Guangzhou Section. He is also a Committee Member of the IEEE CIS Emerging Topics Task Force. He serves as an Associate Editor for the IEEE Transactions on Neural Networks and Learning Systems, and the Complex and Intelligent Systems.
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