报告人：黄辉研究助理

报告题目：Interacting Particle Systems for Optimization: from Particle Swarm Optimization to Consensus-based Optimization

报告摘要：In this talk, we explore the application of metaheuristics through large systems of interacting particles to address complex optimization challenges, with a particular focus on the Particle Swarm Optimization (PSO) method. This approach harnesses the power of collective intelligence, where individual particles adjust their movement based on personal success and the influence of their neighbours, guiding the swarm towards the optimal solution.  We will investigate the continuous model developed by Grassi and Pareschi, presenting evidence of how it ensures convergence to global minimizers and connects to Consensus-based Optimization (CBO) through the limit of zero inertia.

报告人简介：黄辉，奥地利格拉茨大学研究助理，于2017年毕业于清华大学数学科学系，师从简怀玉教授和刘建国教授。博士毕业后曾先后在西蒙弗雷泽大学，慕尼黑工业大学以及卡尔加里大学从事博士后研究工作。主要研究方向为多粒子模型以及他们在最优化领域中的应用，成果发表于J. Mach. Learn. Res., SIAM J. Optim. , SIAM J. Control Optim, M3AS 以及JDE等杂志。

报告时间：2024年10月24号下午16:30-18:30；19：00-20：30

报告形式：腾讯会议；会议号：409-498-356

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