报告题目：Managing Elective Admissions in Hospital Using Robust Optimization

报告人：孟凡文，新加坡国立大学获得运筹学博士学位，目前在新加坡国立健保集团担任运筹优化专家及首席研究分析师。之前他曾在英国南安普敦大学和新加坡国立大学从事运作管理和优化研究工作。孟博士的研究方向包括医疗服务研究，医院资源分配调度管理，疾病预防和治疗决策， 非确定环境下的决策分析，鲁棒优化。孟博士目前担任Pacific Journal of Optimization期刊的副主编。他的一些研究成果发表在医学期刊比如Scientific Reports, Acta Diabetologica, Journal of the Royal Society Interface, Health Systems，以及Operations Research, Mathematics of Operations Research, SIAM Journal on Optimization, Mathematical Programming等运筹学顶级期刊.

时间：2024年6月18日，16:45-17:45

地点：数学院三楼报告厅（304）

摘要：The admission of emergency patients in a hospital is unscheduled, urgent and takes priority over elective patients, who are usually scheduled several days in advance. Hospital beds are a critical resource and the management of elective admissions by enforcing quotas could reduce incidents of shortfall. We propose a distributionally robust optimization approach for managing elective admissions to determine these quotas. Based on an ambiguous set of probability distributions, we propose an optimized budget of variation approach that maximizes the level of uncertainty the admission system can withstand without violating the expected bed shortfall constraint. We solve the robust optimization model by deriving a second order conic problem (SOCP) equivalent of the model. The proposed model is tested in simulations based on real hospital admission data and we report favorable results for adopting the robust optimization models.