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Optimization Support for Senior Design Project Assignments

Author

Listed:
  • Leo Lopes

    (University of Arizona, Tucson, Arizona 85721)

  • Meredith Aronson

    (University of Arizona, Tucson, Arizona 85721)

  • Gary Carstensen

    (University of Arizona, Tucson, Arizona 85721)

  • Cole Smith

    (University of Florida, Gainesville, Florida 32611)

Abstract

Each year, the College of Engineering at the University of Arizona offers senior design projects to approximately 300 seniors. Sponsors provide the university with potential student projects; three to six students from various disciplines must collaborate on each project. Students give the university a rank ordering of their preferred projects. The program manager then selects a subset of the projects, assigns students to projects according to their preferences, and manages other requirements, such as matching sponsor-requested skills and minimizing deviations in team average GPAs. The task of assigning students to projects used to consume untold hours and Post-it notes as the program manager tried to solve the problem manually. Invariably, some students were unhappy because they did not understand why they had been assigned to less-desirable projects. In this paper, we discuss a pragmatic mixed-integer program (MIP) to optimize the solution to this problem. We cover both the modeling challenges and all aspects from design to implementation that were necessary to ensure the system's successful deployment; these include testing, interaction with business processes, user interfaces, and integration. We report the practical benefits the university derived from using our system, and summarize some of the lessons, which we learned as part of our development life cycle, that may be applicable to the development of MIP-based decision-support systems.

Suggested Citation

  • Leo Lopes & Meredith Aronson & Gary Carstensen & Cole Smith, 2008. "Optimization Support for Senior Design Project Assignments," Interfaces, INFORMS, vol. 38(6), pages 448-464, December.
    • Handle: RePEc:inm:orinte:v:38:y:2008:i:6:p:448-464
    DOI: 10.1287/inte.1080.0373
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    References listed on IDEAS

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    1. Rex Cutshall & Srinagesh Gavirneni & Kenneth Schultz, 2007. "Indiana University’s Kelley School of Business Uses Integer Programming to Form Equitable, Cohesive Student Teams," Interfaces, INFORMS, vol. 37(3), pages 265-276, June.
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    Cited by:

    1. Binyamin Krauss & Jon Lee & Daniel Newman, 2013. "Optimizing the Assignment of Students to Classes in an Elementary School," INFORMS Transactions on Education, INFORMS, vol. 14(1), pages 39-44, September.
    2. Thomas L. Magnanti & Karthik Natarajan, 2018. "Allocating Students to Multidisciplinary Capstone Projects Using Discrete Optimization," Interfaces, INFORMS, vol. 48(3), pages 204-216, June.
    3. Stephen Mahar & Wayne Winston & P. Daniel Wright, 2013. "Eli Lilly and Company Uses Integer Programming to Form Volunteer Teams in Impoverished Countries," Interfaces, INFORMS, vol. 43(3), pages 268-284, May-June.
    4. Andrew Bowers & Melissa R. Bowers & Nana Bryan & Paolo Letizia & Spencer Murphy, 2023. "Forming Student Teams to Incorporate Soft Skills and Commonality of Schedule," Interfaces, INFORMS, vol. 53(2), pages 111-127, March.
    5. Nahid Rezaeinia & Julio César Góez & Mario Guajardo, 2022. "Efficiency and fairness criteria in the assignment of students to projects," Annals of Operations Research, Springer, vol. 319(2), pages 1717-1735, December.

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