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An effective greedy heuristic for the Social Golfer Problem

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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.

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Authors and Affiliations

  1. Database and Artificial Intelligence Group, Vienna University of Technology, Vienna, Austria

    Markus Triska & Nysret Musliu

Authors
  1. Markus Triska
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  2. Nysret Musliu
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Correspondence to Markus Triska.

Additional information

The research herein is partially conducted within the competence network Softnet Austria (www.soft-net.at) and funded by the Austrian Federal Ministry of Economics (bm:wa), the province of Styria, the Steirische Wirtschaftsförderungsgesellschaft mbH. (SFG), and the city of Vienna in terms of the center for innovation and technology (ZIT).

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Triska, M., Musliu, N. An effective greedy heuristic for the Social Golfer Problem. Ann Oper Res 194, 413–425 (2012). https://doi.org/10.1007/s10479-011-0866-7

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  • DOI: https://doi.org/10.1007/s10479-011-0866-7

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