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.