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Allocating Games for the NHL Using Integer Programming

Author

Listed:
  • Charles Fleurent

    (University of Montreal, Montreal, Canada)

  • Jacques A. Ferland

    (University of Montreal, Montreal, Canada)

Abstract

In recent years, the National Hockey League (NHL) expanded from 21 to 24 teams. In order to accommodate its scheduling process, the league had to determine new game allocations, that is, the number of times the teams play against each other. This paper introduces a procedure based on integer linear programming that generates several game allocation scenarios that have been presented to the league managers. The model takes into account the constraints specified by the NHL, and the objective function allows the league managers to specify their preference on the distribution of the games.

Suggested Citation

  • Charles Fleurent & Jacques A. Ferland, 1993. "Allocating Games for the NHL Using Integer Programming," Operations Research, INFORMS, vol. 41(4), pages 649-654, August.
    • Handle: RePEc:inm:oropre:v:41:y:1993:i:4:p:649-654
    DOI: 10.1287/opre.41.4.649
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    Citations

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    Cited by:

    1. Bartsch, Thomas & Kröger, Stefan, 1996. "Ein Entscheidungs-Unterstützungs-System zur Erstellung von Spielplänen für die Fußballbundesliga," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 427, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    2. M B Wright, 2009. "50 years of OR in sport," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 161-168, May.
    3. Timothy C. Y. Chan & Justin A. Cho & David C. Novati, 2012. "Quantifying the Contribution of NHL Player Types to Team Performance," Interfaces, INFORMS, vol. 42(2), pages 131-145, April.
    4. Michal Friesl & Liam J. A. Lenten & Jan Libich & Petr Stehlík, 2017. "In search of goals: increasing ice hockey’s attractiveness by a sides swap," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(9), pages 1006-1018, September.
    5. Russell, Robert A. & Urban, Timothy L., 2010. "Multicriteria models for planning power-networking events," European Journal of Operational Research, Elsevier, vol. 207(1), pages 83-91, November.
    6. Durán, Guillermo & Durán, Santiago & Marenco, Javier & Mascialino, Federico & Rey, Pablo A., 2019. "Scheduling Argentina’s professional basketball leagues: A variation on the Travelling Tournament Problem," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1126-1138.
    7. Michal Friesl & Jan Libich & Petr Stehlík, 2020. "Fixing ice hockey’s low scoring flip side? Just flip the sides," Annals of Operations Research, Springer, vol. 292(1), pages 27-45, September.
    8. van Doornmalen, Jasper & Hojny, Christopher & Lambers, Roel & Spieksma, Frits C.R., 2023. "Integer programming models for round robin tournaments," European Journal of Operational Research, Elsevier, vol. 310(1), pages 24-33.
    9. 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.
    10. Alex Krumer & Reut Megidish & Aner Sela, 2020. "The optimal design of round-robin tournaments with three players," Journal of Scheduling, Springer, vol. 23(3), pages 379-396, June.
    11. Deren Çağlayan & Emin Karagözoğlu & Kerim Keskin & Çağrı Sağlam, 2022. "Effort comparisons for a class of four-player tournaments," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 59(1), pages 119-137, July.
    12. Rasmussen, Rasmus V., 2008. "Scheduling a triple round robin tournament for the best Danish soccer league," European Journal of Operational Research, Elsevier, vol. 185(2), pages 795-810, March.
    13. 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.
    14. Kent J. Kostuk & Keith A. Willoughby, 2012. "A Decision Support System for Scheduling the Canadian Football League," Interfaces, INFORMS, vol. 42(3), pages 286-295, June.
    15. Schonberger, J. & Mattfeld, D. C. & Kopfer, H., 2004. "Memetic Algorithm timetabling for non-commercial sport leagues," European Journal of Operational Research, Elsevier, vol. 153(1), pages 102-116, February.
    16. Flavia Bonomo & Andrés Cardemil & Guillermo Durán & Javier Marenco & Daniela Sabán, 2012. "An Application of the Traveling Tournament Problem: The Argentine Volleyball League," Interfaces, INFORMS, vol. 42(3), pages 245-259, June.
    17. Alireza Tajbakhsh & Kourosh Eshghi & Azam Shamsi, 2012. "A hybrid PSO-SA algorithm for the travelling tournament problem," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 6(1), pages 2-25.
    18. Xiajie Yi & Dries Goossens, 2023. "Strategies for dealing with uncertainty in time-relaxed sports timetabling," Annals of Operations Research, Springer, vol. 320(1), pages 473-492, January.

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