The use of constrained optimization to facilitate admission decisions

Weighting models do not adequately represent admission goals. A constrained optimization (CO) decision-analysis model is an alternative that allows a more useful and accurate translation of goals in the admission process. CO allows easy translation of class composition objectives into the model. The author used simulated data to demonstrate the CO technique within a medical-school-admission context. Variables related to class diversity and individual achievement were used to select a class from a simulated final applicant pool. Constraints in the model were evaluated for their effects on the class. The model performed well and yielded significant advantages over weighting equations.