A categorization of observed uses of operational research models for fundamental surprise events: Observations from university operations during COVID-19
研究了大学在COVID-19疫情期间如何调整或创建运筹学模型来应对根本性突发事件，并归纳出五种模型适应类型，帮助理解运筹学在未知危机中的作用。
Operational research (OR) approaches have been increasingly applied to model resilience to surprise events. To model a surprise event, one must understand its characteristics, which then become parameters, decisions, and/or constraints in the model. This means that these models cannot (directly) handle fundamental surprise events, which are events that could not be defined before they happen. However, OR models may be adapted, improvised, or created during a fundamental surprise event, such as the COVID-19 pandemic, to help respond to it. We provide a categorization of observed uses for how OR models were applied by a university in response to the pandemic, thus helping to understand their role during fundamental surprise events. Our categorization includes the following adaptations: adapting data, adding constraints, model switching, pulling from the modeling toolkit, and creating a new model. Each of these adaptations is formally presented, with supporting evidence gathered through interviews with modelers and users involved in the university response to the pandemic.