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Scheduling Major League Baseball Umpires and the Traveling Umpire Problem

Author

Listed:
  • Michael A. Trick

    (Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

  • Hakan Yildiz

    (Eli Broad College of Business, Michigan State University, East Lansing, Michigan 48824)

  • Tallys Yunes

    (School of Business Administration, University of Miami, Coral Gables, Florida 33124)

Abstract

The scheduling needs of umpires and referees differ from the needs of sports teams. In some sports leagues, such as Major League Baseball in the United States, umpires travel throughout the league's territory; they do not have a “home base.” For such leagues, balancing the need to minimize umpire travel and the objective that an umpire should not handle the games of a particular team too frequently is important. We have used our approach, which is based on network optimization and simulated annealing, to successfully schedule Major League Baseball umpires. To develop this approach, we created the traveling umpire problem, which includes the major umpire scheduling issues and also provides a test bed for alternative techniques.

Suggested Citation

  • Michael A. Trick & Hakan Yildiz & Tallys Yunes, 2012. "Scheduling Major League Baseball Umpires and the Traveling Umpire Problem," Interfaces, INFORMS, vol. 42(3), pages 232-244, June.
    • Handle: RePEc:inm:orinte:v:42:y:2012:i:3:p:232-244
    DOI: 10.1287/inte.1100.0514
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    References listed on IDEAS

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    1. James R. Evans, 1988. "A Microcomputer-Based Decision Support System for Scheduling Umpires in the American Baseball League," Interfaces, INFORMS, vol. 18(6), pages 42-51, December.
    2. Adam Farmer & Jeffrey S. Smith & Luke T. Miller, 2007. "Scheduling Umpire Crews for Professional Tennis Tournaments," Interfaces, INFORMS, vol. 37(2), pages 187-196, April.
    3. Rasmussen, Rasmus V. & Trick, Michael A., 2008. "Round robin scheduling - a survey," European Journal of Operational Research, Elsevier, vol. 188(3), pages 617-636, August.
    4. Dirk Briskorn, 2008. "Sports Leagues Scheduling," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-540-75518-0, October.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Yun-Chia Liang & Yen-Yu Lin & Angela Hsiang-Ling Chen & Wei-Sheng Chen, 2021. "Variable Neighborhood Search for Major League Baseball Scheduling Problem," Sustainability, MDPI, vol. 13(7), pages 1-18, April.
    2. Toffolo, Túlio A.M. & Wauters, Tony & Van Malderen, Sam & Vanden Berghe, Greet, 2016. "Branch-and-bound with decomposition-based lower bounds for the Traveling Umpire Problem," European Journal of Operational Research, Elsevier, vol. 250(3), pages 737-744.
    3. Alan T. Murray & Antonio Ortiz & Seonga Cho, 2022. "Enhancing strategic defensive positioning and performance in the outfield," Journal of Geographical Systems, Springer, vol. 24(2), pages 223-240, April.
    4. Eric Fesselmeyer, 2021. "The impact of temperature on labor quality: Umpire accuracy in Major League Baseball," Southern Economic Journal, John Wiley & Sons, vol. 88(2), pages 545-567, October.
    5. Michael J. Fry & Jeffrey W. Ohlmann, 2012. "Introduction to the Special Issue on Analytics in Sports, Part II: Sports Scheduling Applications," Interfaces, INFORMS, vol. 42(3), pages 229-231, June.
    6. Elizabeth L. Bouzarth & Benjamin C. Grannan & John M. Harris & Kevin R. Hutson, 2022. "Scheduling the Valley Baseball League," Interfaces, INFORMS, vol. 52(2), pages 189-197, March.
    7. Mancini Simona & Isabello Andrea, 2014. "Fair referee assignment for the Italian soccer serieA," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(2), pages 153-160, June.
    8. B. Madhu Rao & Petros Xanthopoulos & Qipeng Phil Zheng, 2020. "Case Article—DeLand Crayon Company: An Application of the Traveling Salesman Problem to Production Scheduling with Sequence-Dependent Setup Times," INFORMS Transactions on Education, INFORMS, vol. 20(2), pages 93-98, January.
    9. Wauters, Tony & Van Malderen, Sam & Vanden Berghe, Greet, 2014. "Decomposition and local search based methods for the traveling umpire problem," European Journal of Operational Research, Elsevier, vol. 238(3), pages 886-898.
    10. de Oliveira, Lucas & de Souza, Cid C. & Yunes, Tallys, 2014. "Improved bounds for the traveling umpire problem: A stronger formulation and a relax-and-fix heuristic," European Journal of Operational Research, Elsevier, vol. 236(2), pages 592-600.
    11. Zachary Steever & Chase Murray & Junsong Yuan & Mark Karwan & Marco Lübbecke, 2022. "An Image-Based Approach to Detecting Structural Similarity Among Mixed Integer Programs," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 1849-1870, July.
    12. Guillermo Durán, 2021. "Sports scheduling and other topics in sports analytics: a survey with special reference to Latin America," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 125-155, April.
    13. Özlü, Oğuzhan & Sokol, Joel, 2016. "An optimization approach to designing a baseball scout network," European Journal of Operational Research, Elsevier, vol. 255(3), pages 948-960.
    14. Guillermo Durán & Mario Guajardo & Facundo Gutiérrez, 2022. "Efficient referee assignment in Argentinean professional basketball leagues using operations research methods," Annals of Operations Research, Springer, vol. 316(2), pages 1121-1139, September.
    15. Xue, Li & Luo, Zhixing & Lim, Andrew, 2015. "Two exact algorithms for the traveling umpire problem," European Journal of Operational Research, Elsevier, vol. 243(3), pages 932-943.
    16. Túlio A. M. Toffolo & Jan Christiaens & Frits C. R. Spieksma & Greet Vanden Berghe, 2019. "The sport teams grouping problem," Annals of Operations Research, Springer, vol. 275(1), pages 223-243, April.

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