Recent Progress in MOEA/D
张青富   Qingfu Zhang
报告人照片   Qingfu Zhang is a Professor at the Department of Computer Science, City University of Hong Kong. His main research interests include evolutionary computation, optimization, neural networks, data analysis, and their applications. Professor Zhang is an Associate Editor of the IEEE Transactions on Evolutionary Computation and the IEEE Transactions Cybernetics. He is on the list of the Thomson Reuters 2016 and 2017 highly cited researchers in computer science. He is a Fellow of IEEE. He is a Changjiang chair professor and was selected in 1000 talent program in 2015.
  Multiobjective Evolutionary Computation has been a major research topic in the field of evolutionary computation for many years. It has been generally accepted that combination of evolutionary algorithms and traditional optimization methods should be a next generation multiobjective optimization solver. Decomposition methods have been well used and studied in traditional multiobjective optimization. It is well known that the Pareto optimal solution set of a continuous multiobjective problem often exhibits some regularity. In this talk, I will describe MOEA/D and its recent progress. MOEA/D decomposes a multiobjective problem into a number of subtasks, and then solves them in a collaborative manner. It provides a very natural bridge between multiobjective evolutionary algorithms and traditional decomposition methods. It has been a commonly used evolutionary algorithmic framework in recent years.
报告时间:2018年04月02日10时00分    报告地点:西区电二楼208
报名截止日期:2018年04月02日    可选人数:40