​​The Fourth International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration 

Shantou, China  

December 18-19, 2020

ICIICII 2020
Invited Speech

​​

Local landscape

​​

Co-sponsors

Hui Li, PhD,Professor


School of Mathematics and Statistics (SMS), Xi'an Jiaotong University



Title: On the population strategies in MOEA/D



Biography
     Dr. Hui Li is a Professor with the School of Mathematics and Statistics (SMS), Xi'an Jiaotong University(XJTU). He is currently the dean of the department of computing science in SMS/XJTU. He is also a senior IEEE member. His major research interests include evolutionary computation, multiobjective optimization, and machine learning. Prof. Li has published more than thirty academic papers in some high-quality conferences and journals of computational intelligence, including IEEE Trans. on Evolutionary Computation, IEEE Trans. on Neural Network and Learning System, IEEE Trans. on Cybernetics. He won the 2010 outstanding paper award of IEEE Trans. on Evolutionary Computation as one of the inventors for MOEA/D, which has been cited more than 4,900 times in terms of google scholar citation.
  • The bird's-eye view of Shantou University
  • Nan’ao  Island
  • Nan'ao Bridge
  • Zhongshan Pavilion
  • Shantou Coastal Corridor
  • Lotus Pond
  • Gentleman Sculpture Group
Hailin Liu, PhD,Professor


School of Applied Mathematics at the Guangdong Universityof Technology



Title: Evolutionary Multi- and Many-Objective Optimization Algorithm 

         Using Region Decomposition





Abstract
      An effective allocation of search effort is important in multi-objective optimization, particularly in many-objective optimization problems. This talk will discuss an adaptive search effort allocation strategy for MOEA/D-M2M for challenging Many-Objective Optimization Problems (MaOPs). This talk will introduce adaptively adjusts the subregions of its subproblems by detecting the importance of different objectives in an adaptive manner. More specifically, it periodically resets the subregion setting based on the distribution of the current solutions in the objective space such that the search effort is not wasted on unpromising regions. This talk will cover characterizes an imbalanced MOP by clearly defining properties and indicating the reasons for the existing EMO algorithms’ difficulties in solving them. 

Biography
     Hai-Lin Liu (M’10-SM’19) is a Full Professor of School of Applied Mathematics at the Guangdong Universityof Technology. He received the B.S. degree in mathematics from Henan Normal U niversity, Xinxiang, China, the M.S degree in applied mathematics from Xidian University, Xi’ an, China, the Ph.D. degree in control theory and engineering from South China University of Technology, Guangzhou, China, and Post-doctor in the Institute of Electronic and Information, South China University of Technology, Guangzhou, China. His research interests include evolutionary computation and optimization, wireless network planning and optimization, and their applications. He has published over 100 research papers in journals and conferences. Prof.  Liu currently serves as an Associate Editor of the IEEE Transactions on Evolutionary Computation.
Previous
Next
Last
First