2021年5月7日,【明理講堂2021年第22期】有幸邀請到瑞士洛桑聯邦理工學院（EPFL）Daniel Kuhn教授帶來題為“Optimization in the Face of Uncertainty”的學術報告。報告采用騰訊會議的形式。管理與經濟學院教師、研究生以及校外研究學者等300多名師生參加了本次講座，主持人為管理與經濟學院管理工程系張玉利副教授。
本次報告中，Daniel Kuhn教授圍繞面向不確定性的優化問題進行了多方面的分享。首先，Daniel Kuhn教授以簡單的確定性優化問題為基礎，引入不確定性優化問題，并通過多個生動的例子，強調不確定性因素在各類問題中的重要性。Daniel Kuhn教授指出，隨機規劃模型和風險感知規劃模型在解決不確定性問題時具有局限性，存在著高維問題求解慢、求解存在偏差、統計估計難以實現等困難，且隨機參數的精確分布往往不可知，存在“關于不確定性的不確定性”。進而，Daniel Kuhn教授介紹了分布式魯棒優化模型，該模型能夠在解決不確定性優化問題時達到“雙贏”。一方面，分布式魯棒優化模型能夠得到更好的決策，另一方面，也能解決隨機和風險感知規劃模型面臨的求解難題。最后，Daniel Kuhn教授還指出，當問題存在模糊性時，做出隨機決策往往是較優的。
報告結束后，Daniel Kuhn教授和參會師生展開了熱烈的討論和交流，報告反響熱烈，受到了廣大師生的一致好評！
附：Daniel Kuhn教授簡介
Daniel Kuhn is full Professor of Operations Research at the College of Management of Technology atécole polytechnique fédérale de Lausanne, Switzerland (EPFL), where he holds the Chair of Risk Analytics and Optimization (RAO). Before joining EPFL, he was a faculty member at Imperial College London (2007–2013) and a postdoctoral researcher at Stanford University (2005–2006). He received a Ph.D. in Economics from the University of St. Gallen in 2004 and an M.Sc. in Theoretical Physics from ETH Zürich in 1999. His research interests revolve around robust optimization and stochastic programming. He serves as the area editor for continuous optimization for Operations Research and as an associate editor for several other journals including Management Science, Mathematical Programming, Mathematics of Operations Research and Operations Research Letters.
