IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v43y2013i3p268-284.html
   My bibliography  Save this article

Eli Lilly and Company Uses Integer Programming to Form Volunteer Teams in Impoverished Countries

Author

Listed:
  • Stephen Mahar

    (Department of Management and Operations, Villanova School of Business, Villanova University, Villanova, Pennsylvania 19085)

  • Wayne Winston

    (Department of Operations and Decision Technologies, Kelley School of Business, Indiana University, Bloomington, Indiana 47405)

  • P. Daniel Wright

    (Department of Management and Operations, Villanova School of Business, Villanova University, Villanova, Pennsylvania 19085)

Abstract

Each year, Eli Lilly and Company (Lilly) offers its worldwide employees the opportunity to participate in paid volunteer teams serving communities in impoverished countries. The company’s Connecting Hearts Abroad service program gives employees a unique opportunity to take part in service trips aimed at improving global health. Lilly annually offers about 23 trips, enabling employees to serve some of the world’s most resource-constrained regions where people lack basic resources or access to healthcare. A selection committee at Lilly manually forms volunteer teams from a large pool of applicants. Unfortunately, the manual selection process is time consuming and often fails to meet employee preference or adequately represent some applicant groups. This paper describes how we developed a mathematical programming model to improve Lilly’s process of volunteer selection. We incorporated the model into a decision support tool that assigns applicants to volunteer assignments and maximizes the chosen volunteers’ preferences under constraints that help ensure fair team compositions. Running the model against the prior year’s applicant data pool took less than two minutes to configure teams such that all volunteers received their first-choice assignment. The automated decision support system also provides a more consistent method of configuring teams that appears fair to the applicants.

Suggested Citation

  • 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.
  • Handle: RePEc:inm:orinte:v:43:y:2013:i:3:p:268-284
    DOI: 10.1287/inte.2013.0679
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.2013.0679
    Download Restriction: no

    File URL: https://libkey.io/10.1287/inte.2013.0679?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. K R Baker & S G Powell, 2002. "Methods for assigning students to groups: a study of alternative objective functions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(4), pages 397-404, April.
    2. Gary R. Reeves & Edgar P. Hickman, 1992. "Assigning MBA Students to Field Study Project Teams: A Multicriteria Approach," Interfaces, INFORMS, vol. 22(5), pages 52-58, October.
    3. 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.
    4. 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.
    5. Dmitry Krass & Anton Ovchinnikov, 2006. "The University of Toronto’s Rotman School of Management Uses Management Science to Create MBA Study Groups," Interfaces, INFORMS, vol. 36(2), pages 126-137, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Escallon-Barrios, Mariana & Noham, Reut & Smilowitz, Karen, 2024. "Dual mode scheduling in volunteer management," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. Thomas L. Magnanti & Karthik Natarajan, 2018. "Allocating Students to Multidisciplinary Capstone Projects Using Discrete Optimization," Interfaces, INFORMS, vol. 48(3), pages 204-216, June.
    4. 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.
    5. Theresa M. Roeder & Robert M. Saltzman, 2014. "Schedule-Based Group Assignment Using Constraint Programming," INFORMS Transactions on Education, INFORMS, vol. 14(2), pages 63-72, February.
    6. 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.
    7. Akkan, Can & Erdem Külünk, M. & Koçaş, Cenk, 2016. "Finding robust timetables for project presentations of student teams," European Journal of Operational Research, Elsevier, vol. 249(2), pages 560-576.
    8. Sharan Srinivas & Mohammadmahdi Alizadeh & Nathaniel D.Bastian, 2017. "Optimizing Student Team and Job Assignments for the Holy Family Academy," Interfaces, INFORMS, vol. 47(2), pages 163-174, April.
    9. Arne Schulz, 2023. "The balanced maximally diverse grouping problem with integer attribute values," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-27, July.
    10. Johnes, Jill, 2015. "Operational Research in education," European Journal of Operational Research, Elsevier, vol. 243(3), pages 683-696.
    11. Krass, Dmitry & Ovchinnikov, Anton, 2010. "Constrained group balancing: Why does it work," European Journal of Operational Research, Elsevier, vol. 206(1), pages 144-154, October.
    12. Arne Schulz, 2024. "Efficient neighborhood evaluation for the maximally diverse grouping problem," Annals of Operations Research, Springer, vol. 341(2), pages 1247-1265, October.
    13. Z P Fan & Y Chen & J Ma & S Zeng, 2011. "Erratum: A hybrid genetic algorithmic approach to the maximally diverse grouping problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1423-1430, July.
    14. Ansari, Azadeh & Farrokhvar, Leily & Kamali, Behrooz, 2021. "Integrated student to school assignment and school bus routing problem for special needs students," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    15. Arne Schulz, 2022. "A new mixed-integer programming formulation for the maximally diverse grouping problem with attribute values," Annals of Operations Research, Springer, vol. 318(1), pages 501-530, November.
    16. Saber, Hussein M. & Ghosh, Jay B., 2001. "Assigning students to academic majors," Omega, Elsevier, vol. 29(6), pages 513-523, December.
    17. Z P Fan & Y Chen & J Ma & S Zeng, 2011. "A hybrid genetic algorithmic approach to the maximally diverse grouping problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 92-99, January.
    18. Schulz, Arne, 2021. "The balanced maximally diverse grouping problem with block constraints," European Journal of Operational Research, Elsevier, vol. 294(1), pages 42-53.
    19. Fernández, Elena & Kalcsics, Jörg & Nickel, Stefan, 2013. "The maximum dispersion problem," Omega, Elsevier, vol. 41(4), pages 721-730.
    20. Ball Michael O & Halper Russell, 2009. "Scramble Teams for the Pinehurst Terrapin Classic," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(2), pages 1-25, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orinte:v:43:y:2013:i:3:p:268-284. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.