报告题目： Decomposition Based Multiobjective Evolutionary Computation

报告人： 张青富 讲座教授 香港城市大学

照片：

邀请人： 高卫峰

报告时间： 2019-05-27（周一） 10:00

报告地点： 信远楼II206我院报告厅

报告人简介：张青富教授现为香港城市大学计算科学系讲座教授, 主要研究领域包括：进化计算、数学规划、神经网络、统计数据分析及其应用。张教授是香港城市大学启发式优化研究（Metaheuristic Optimization Research (MOP)）课题组的带头人。该课题组提出的基于分解的多目标进化算法—MOEA/D，是当前多目标进化算法领域非常流行的算法框架，近年来受到了国内外学者的关注和研究。

张青富教授为IEEE Fellow，是IEEE Transactions on Evolutionary Computation和 IEEE Transactions on Cybernetics等计算智能领域权威期刊的副主编，同时也是其他多个国际期刊的编委会成员，是计算智能领域顶级国际会议的多届分会主席，并且获得了2010年IEEE Transactions on Evolutionary Computation的优秀论文奖（Outstanding Paper Award）。2016、2017、2018年入选Web of Science公布的计算科学领域的高引学者。

报告摘要：

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. In this talk, I will describe MOEA/D algorithmic framework. MOEA/D decomposes a multiobjective problem into a number of subtasks, and then solves them in a collaborative manner. MOEA/D 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. I will explain the basic ideas behind MOEA/D and some recent developments. I will also outline some possible research issues in multiobjective evolutionary computation.