主题： 鲁棒可扩展的基础设施网络韧性优化方法分析

主讲人：方一平 副教授

时间：7月6日（周四）下午14:30

地点：清水河校区主楼C1-213

专家介绍：

方一平，副教授，博导，现就职于法国巴黎萨克雷大学（University of Paris-Saclay）中央理工-高等电力学院（CentraleSupelec）工业工程实验室。方教授及其团队主要研究方向为信息物理系统风险和弹性建模分析、维修优化、随机和鲁棒优化、强化学习，作为Principal Investigator承担法国自然科学基金，欧盟玛丽·斯克沃多夫斯卡-居里，以及法国电力（EDF）、法国高铁（SNCF）、法国电信（Orange）等多项研究课题。其研究成果发表于European Journal of Operational Research, Renewable and Sustainable Energy Review, IEEE Transactions on Smart Grids, IEEE Transactions on Reliability, Risk Analysis, Reliability Engineering & System Safety, Computer-Aided Civil and Infrastructure Engineering等期刊，研究论文共计30余篇。

报告内容简介：

This seminar aims to explore the application of prescriptive analytics in enhancing infrastructure network resilience, with a focus on two key aspects. First, the seminar will introduce distributionally robust optimization as a strategy for ex-ante planning under ambiguous failure scenarios. Exemplary case studies will be presented by the speaker to demonstrate the efficacy of this approach. Second, the seminar will delve into the use of deep reinforcement learning to improve ex-post response and recovery planning for large-scale real-world systems. The speaker will discuss the challenges posed by deep uncertainties and computational complexity, and provide insights into future research directions.