报告人: Pierre Pinson (Imperial College London)

时间：4月25日（周五）10:00-11:30

主持人：何冠楠 研究员

地点：betway唯一官方网站1号楼210报告厅

Abstract: Forecasts are most often there to be used as input to decision-making. And, since forecasts are never perfect, it appears natural to ask oneself how to make decisions given their uncertainty. A large body of scientific literature has developed within probabilistic forecasting and stochastic optimisation, in response to such challenges. We will focus on the specific case of newsvendor problems, which are common within procurement, logistics and energy trading for instance. However, we will extend the discussion to the case where one does not trust the probabilistic forecasts used as input, while also being unsure about the actual loss function at hand. After introducing the Bernouilli newsvendor problem, we present more general solutions to the newsvendor problem, when one does not trust the forecasts, for both decision variable and loss function parameters. A renewable energy trading example will allow illustrating the interest of the approach.

Short Bio: Pierre Pinson is a Professor at Imperial College London, Dyson School of Design Engineering, and the Deputy-head of School. He is also a chief scientist at Halfspace, an affiliated professor at the Technical University of Denmark, and an associate research fellow at Aarhus University (CoRE). He is the Editor-in-Chief of the International Journal of Forecasting. He is an IEEE Fellow, as well as an INFORMS member and an IIF director. He is on the Highly-cited Researcher list of WoS/Clarivate over 2019-2023 (cross-field category) for numerous high-impact works in statistics, meteorology, economics and power/energy engineering. He is seen as a leading figure internationally within predictive analytics. He has received the INFORMS Franz Edelman Award 2024 for outstanding achievements within operations research, analytics and management science.

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