Optimizing Student Team and Job Assignments for the Holy Family Academy

Sharan Srinivas (), Mohammadmahdi Alizadeh () and Nathaniel D.Bastian ()
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Sharan Srinivas: The Pennsylvania State University, University Park, Pennsylvania 16802
Mohammadmahdi Alizadeh: The Pennsylvania State University, University Park, Pennsylvania 16802
Nathaniel D.Bastian: The Pennsylvania State University, University Park, Pennsylvania 16802

Interfaces, 2017, vol. 47, issue 2, 163-174

Abstract: Holy Family Academy (HFA) is a private Catholic high school in which funding for students is provided largely by organizations, many of whom sponsor work-study positions for students. Each student must work one day per week. HFA seeks to group its students into teams based on the day of work-study and then assign students to specific jobs. We develop weighted mixed-integer linear goal-programming models as a means of decision support for HFA to assign students to teams for each school year, and to assign each student on each team to a job. The models increase the transparency of student assignments for HFA administrators, while effectively determining well-balanced, diversified student team and job assignments. The decision support tool provides tremendous value to HFA in terms of time and reproducibility, requiring only minutes to solve, rather than weeks. This enables HFA to conduct quick what-if analyses, such as varying the number of students assigned to each team, a task that was impossible to perform manually.

Date: 2017
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