报告题目：Multiobjective optimization evolutionary algorithms Based Decomposition

报告时间：2022年4月20日（周三），上午10点-11点

腾讯会议号：670-477-087；会议密码：0420

报告摘要：

Multiobjective optimization can be found in many real-life applications. Multiobjective optimization evolutionary algorithms (MOEA) have been widely accepted as a main methodology for dealing with multiobjecitve optimization. Multiobjective optimization evolutionary algorithms Based Decomposition (MOEA/D) is one of the two major MOEA frameworks. Over the last ten years, MOEA/D has received much research effort from the evolutionary computation community. Many successful applications of MOEA/D have been reported. In this talk, I will explain the motivation, ideas and basic components in MOEA/D. I will also introduce some recent developments on MOEA/D.

报告人简介：

张青富，香港城市大学计算智能讲座教授，IEEE Fellow，国家级人才。张教授曾获得2010年IEEE Transactions on Evolutionary Computation杰出论文奖，并从2016年至2020年连续五年入选计算机科学领域的高被引学者。张教授长期从事计算智能、多目标优化及机器学习方面的研究。其所提出的MOEA/D已成为进化多目标优化领域最常用的算法框架之一。