Unifying Approaches to
Optimization under Uncertainty
报告专家：Christiane Tammer教授 （马丁路德大学）
报告时间：2024年11月16日（周六）下午5:00-6:00
报告地点：四川大学数学学院西109
报告摘要：Most optimization problems involve uncertain data due to measurement errors, unknown future developments and modeling approximations. Stochastic optimization assumes that the uncertain parameter is probabilistic. An other approach is called robust optimization which expects the uncertain parameter to belong to a set that is known prior. In this talk, we consider scalar optimization problems under uncertainty with infinite scenario sets. We apply methods from vector optimization in general spaces, set-valued optimization and scalarization techniques to derive necessary optimality conditions for solutions of robust optimization problems.
专家简介：Christiane Tammer，德国马丁路德大学 (Martin-Luther-University) 数学研究所教授。在德国Technical University Merseburg获得博士学位后，曾在University Leipzig和Royal Military College of Canada任客座教授，自1998以来一直在Martin-Luther-University任教授, 曾任学术研究主任。在极小点理论和变分原理、变分不等式和逆问题、广义凸分析和对偶理论、逼近理论和鲁棒优化、向量优化和集优化方面做过开创性和系统性的工作。发表学术论文多篇，并已出版多部专著。现任《Optimization》等3种国际学术期刊主编（联合主编），多种国际学术期刊编委。
