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An improved SAT formulation for the social golfer problem

Author

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  • Markus Triska
  • Nysret Musliu

Abstract

The Social Golfer Problem (SGP) is a sports scheduling problem that exhibits a lot of symmetry and has recently attracted significant attention. In this paper, we first revisit an existing SAT encoding for the SGP and correct some of its clauses. We then propose a change in the encoding that significantly reduces the number of variables for all instances. We achieve considerable performance improvements when solving many SGP instances with common SAT solvers using local search and complete backtracking. This makes SAT formulations a more promising approach for solving the SGP than previously. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Markus Triska & Nysret Musliu, 2012. "An improved SAT formulation for the social golfer problem," Annals of Operations Research, Springer, vol. 194(1), pages 427-438, April.
    • Handle: RePEc:spr:annopr:v:194:y:2012:i:1:p:427-438:10.1007/s10479-010-0702-5
    DOI: 10.1007/s10479-010-0702-5
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    Cited by:

    1. Frédéric Lardeux & Eric Monfroy & Broderick Crawford & Ricardo Soto, 2015. "Set constraint model and automated encoding into SAT: application to the social golfer problem," Annals of Operations Research, Springer, vol. 235(1), pages 423-452, December.
    2. Martin Mariusz Lester, 2022. "Pseudo-Boolean optimisation for RobinX sports timetabling," Journal of Scheduling, Springer, vol. 25(3), pages 287-299, June.
    3. Schmand, Daniel & Schröder, Marc & Vargas Koch, Laura, 2022. "A greedy algorithm for the social golfer and the Oberwolfach problem," European Journal of Operational Research, Elsevier, vol. 300(1), pages 310-319.

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