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An effective greedy heuristic for the Social Golfer Problem

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  • Markus Triska
  • Nysret Musliu

Abstract

The Social Golfer Problem (SGP) is a combinatorial optimization problem that exhibits a lot of symmetry and has recently attracted significant attention. In this paper, we present a new greedy heuristic for the SGP, based on the intuitive concept of freedom among players. We use this heuristic in a complete backtracking search, and match the best current results of constraint solvers for several SGP instances with a much simpler method. We then use the main idea of the heuristic to construct initial configurations for a metaheuristic approach, and show that this significantly improves results obtained by local search alone. In particular, our method is the first metaheuristic technique that can solve the original problem instance optimally. We show that our approach is also highly competitive with other metaheuristic and constraint-based methods on many other benchmark instances from the literature. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Markus Triska & Nysret Musliu, 2012. "An effective greedy heuristic for the Social Golfer Problem," Annals of Operations Research, Springer, vol. 194(1), pages 413-425, April.
    • Handle: RePEc:spr:annopr:v:194:y:2012:i:1:p:413-425:10.1007/s10479-011-0866-7
    DOI: 10.1007/s10479-011-0866-7
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    Cited by:

    1. Martin Mariusz Lester, 2022. "Pseudo-Boolean optimisation for RobinX sports timetabling," Journal of Scheduling, Springer, vol. 25(3), pages 287-299, June.
    2. 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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