arXiv subjects

Steven Foster

Publications and source records attributed to Steven Foster.

2 recordsLinked to original sources

arXiv2022

A Framework for Operations Research Model Use in Resilience to Fundamental Surprise Events: Observations from University Operations during COVID-19

Operations research (OR) approaches have been increasingly applied to model the resilience of a system to surprise events. In order to model a surprise event, one must have an understanding of its characteristics, which then become parameters, decisions, and/or constraints in the resulting 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 framework for how OR models were applied by a university in response to the pandemic, thus helping to understand the role of OR models during fundamental surprise events. Our framework 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. We discuss the implications of this framework for both OR and resilience.

cs.CY↗

arXiv2022

Developing Optimization Models with Cognitive Systems Engineering

One goal of applied operations research is to improve decisions in practice. This requires modelers and stakeholders to have a shared understanding of the system and for the developed model to reflect the system's core dynamics. There are four areas to address: the underlying problem must be understood, the mathematical formulation of the problem must be representative of the system at hand, the data must be appropriate, and the model-generated recommendations must be understandable by the stakeholders. While developing models, operations researchers may primarily rely on past experience in model development, rather than underlying theory, to guide decisions on how to include stakeholders in the modeling process. In parallel, the field of Cognitive Systems Engineering has developed methodologies and practices to understand systems, stakeholder needs, and environments. To improve the rigor of the "application" in applied operations research, we present a framework to integrate Cognitive Systems Engineering methods with optimization model development. We apply the integrated framework to a case study of locating hand sanitizer stations in response to COVID-19 at a large academic institution.

math.OC↗