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Maximizing Diversity in the Engineering Global Leadership Cultural Families

Author

Listed:
  • Kayse Lee Maass

    (University of Michigan, Ann Arbor, Michigan 48109)

  • Vera Mann Hey Lo

    (University of Michigan, Ann Arbor, Michigan 48109)

  • Anna Weiss

    (The Bar Bakery, Sacramento, California 95811)

  • Mark S. Daskin

    (University of Michigan, Ann Arbor, Michigan 48109)

Abstract

We present a new formulation for assigning students to groups to maximize the diversity within each group. We compare its solution to that of the well-known linearized maximally diverse grouping problem. The new formulation minimizes similar student attributes within a group by penalizing the deviations from the target number of students with each attribute within each group. We apply the model to the task of assigning University of Michigan Engineering Global Leadership (EGL) Honors Program students to cultural families. The EGL program implemented the results of the model with minimal changes.

Suggested Citation

  • Kayse Lee Maass & Vera Mann Hey Lo & Anna Weiss & Mark S. Daskin, 2015. "Maximizing Diversity in the Engineering Global Leadership Cultural Families," Interfaces, INFORMS, vol. 45(4), pages 293-304, August.
    • Handle: RePEc:inm:orinte:v:45:y:2015:i:4:p:293-304
    DOI: 10.1287/inte.2015.0796
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    References listed on IDEAS

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    Cited by:

    1. Talmor, Irit, 2022. "Solving the problem of maximizing diversity in public sector teams," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    2. 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.
    3. Pitchaya Wiratchotisatian & Hoda Atef Yekta & Andrew C. Trapp, 2022. "Stability Representations of Many-to-One Matching Problems: An Integer Optimization Approach," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3325-3343, November.

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