The admission office in almost every four‐year college faces the challenge of determining the number of students to be admitted each year, because only a small percentage of the students enroll after being accepted (called yield rate). The national average yield rate in four‐year colleges and universities has declined. At The Citadel under normal circumstances, it is even more challenging since the cadets are required to stay on campus where the beds in the barracks are limited. An insufficient number of freshmen enrolled at The Citadel result in a loss of revenue, and too many freshmen enrolled results in shortage of beds. In this paper, we conduct a case study and apply the overbooking model in revenue management to find the optimal admission limit at The Citadel. We perform a computation experiment on the enrollment data to obtain the optimal admission limit for the academic year 2020–2021. Also, over the last five years, we have compared the admission limit obtained using the risk‐based policy to the admission limit obtained using the deterministic heuristic method, and with the actual admission number from the historical data. The results of this case study can be used by the admission office at The Citadel to measure its past performance, identify strategies, and make informed admission decisions in the near future.

中文翻译：

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超额预订模型在The Citadel大学录取中的应用

几乎每四年制大学的招生办公室都面临着确定每年招生人数的挑战，因为只有一小部分学生被录取后才入学（称为合格率））。四年制大学的全国平均生产率下降了。在正常情况下，在Citadel城堡，挑战更加严峻，因为学员必须待在营房床位有限的校园里。进入The Citadel的新生人数不足会导致收入损失，而新生人数过多则会导致床位短缺。在本文中，我们进行了一个案例研究，并将超额预订模型应用于收入管理，以找到The Citadel的最佳入学限制。我们对入学数据进行了计算实验，以获得2020-2021学年的最佳入学限制。此外，在过去五年中，我们将使用基于风险的策略获得的入学限制与使用确定性启发式方法获得的入学限制进行了比较，以及历史数据中的实际入场人数。该案例研究的结果可供The Citadel的招生办公室使用，以衡量其过去的表现，确定策略并在不久的将来做出明智的招生决策。