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Practice Summary: Managing Capacity at the University of Mary Washington’s College of Business

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  • Christopher Garcia

    (College of Business, University of Mary Washington, Fredericksburg, Virginia 22401)

Abstract

The University of Mary Washington’s College of Business (COB) has experienced a period of sustained growth in demand for its programs over the past eight years. To properly manage growth as the organization approaches capacity, this has necessitated both an optimal utilization of its faculty resources across its programs and an understanding of key bottlenecks and resource imbalances. This was addressed by modeling the problem as a multiobjective max-flow system with pooled resources. A spreadsheet model was developed to determine the optimal allocation of resources across the programs and allow interactive exploration of different scenarios based on different assumptions. The tool also allowed the COB to precisely identify and quantify bottlenecks and resource excesses. This work has provided critical inputs necessary for future course planning and hiring strategies.

Suggested Citation

  • Christopher Garcia, 2019. "Practice Summary: Managing Capacity at the University of Mary Washington’s College of Business," Interfaces, INFORMS, vol. 49(2), pages 167-171, March.
  • Handle: RePEc:inm:orinte:v:49:y:2019:i:2:p:167-171
    DOI: 10.1287/inte.2019.0986
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    References listed on IDEAS

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    1. Colin O. Benjamin & Ike C. Ehie & Yildirim Omurtag, 1992. "Planning Facilities at the University of Missouri-Rolla," Interfaces, INFORMS, vol. 22(4), pages 95-105, August.
    2. Clarence H. Martin, 2004. "Ohio University's College of Business Uses Integer Programming to Schedule Classes," Interfaces, INFORMS, vol. 34(6), pages 460-465, December.
    3. Amy Cohn & Sarah Root & Carisa Kymissis & Justin Esses & Niesha Westmoreland, 2009. "Scheduling Medical Residents at Boston University School of Medicine," Interfaces, INFORMS, vol. 39(3), pages 186-195, June.
    4. Sang M. Lee & Edward R. Clayton, 1972. "A Goal Programming Model for Academic Resource Allocation," Management Science, INFORMS, vol. 18(8), pages 395-408, April.
    5. Thomas L. Magnanti & Karthik Natarajan, 2018. "Allocating Students to Multidisciplinary Capstone Projects Using Discrete Optimization," Interfaces, INFORMS, vol. 48(3), pages 204-216, June.
    6. Timothy R. Hinkin & Gary M. Thompson, 2002. "SchedulExpert: Scheduling Courses in the Cornell University School of Hotel Administration," Interfaces, INFORMS, vol. 32(6), pages 45-57, December.
    7. Gerardo Gonzalez & Christopher Richards & Alexandra Newman, 2018. "Optimal Course Scheduling for United States Air Force Academy Cadets," Interfaces, INFORMS, vol. 48(3), pages 217-234, June.
    8. James C. Hearn & Darrell R. Lewis & Lincoln Kallsen & Janet M. Holdsworth & Lisa M. Jones, 2006. "“Incentives for Managed Growth”: A Case Study of Incentives-Based Planning and Budgeting in a Large Public Research University," The Journal of Higher Education, Taylor & Francis Journals, vol. 77(2), pages 286-316, March.
    9. E. Wailand Bessent & Authella M. Bessent, 1980. "Student Flow in a University Department: Results of a Markov Analysis," Interfaces, INFORMS, vol. 10(2), pages 52-59, April.
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