报告题目：机会约束优化问题的等价转化、逼近及其应用

报告人：彭深助理教授

邀请人：刘三阳教授

报告时间：2022年4月12日（周二）14:00——16:00

腾讯会议ID：282-466-867

报告人简介：彭深，理学博士，于2012年获西安交通大学信息与计算科学专业学士学位，2019年分别获得法国巴黎萨克雷大学计算机专业博士学位，以及西安交通大学计算数学专业博士学位。2019年至2021年在瑞典皇家理工学院从事博士后工作。主要从事随机优化、鲁棒优化方法相关方面的研究，尤其是在机会约束优化和分布式鲁棒机会约束优化的等价转化，逼近以及在复杂工程问题中的应用方面取得了一系列的研究成果。已在《European Journal of Operational Research》，《Computational Optimization and Applications》，《Journal of Global Optimization》，《Journal of Optimization Theory and Applications》以及《Operations Research Letters》等国际权威学术期刊上发表高水平SCI论文8篇。

报告摘要：As an important research topic of stochastic programming, chance constrained optimization problem has attracted a great attention of many researchers. Since chance constraint was proposed in 1959, it has been applied widely in engineering, military, economics, finance and many other fields. Recently, with the development of machine learning and optimization techniques, chance constraint has also been applied in artificial intelligence fields such as support vector machine and reinforcement learning. In this talk, chance constraint will beinvestigatedfrom the following three perspectives: the equivalent reformulation, tractable approximation, and the applications in some practical problems, such as portfolio selection, recourse allocation and machine learning. In addition, some potential applications in other engineering problems will also be discussed.

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