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Grouping and scheduling multiple sports leagues: an integrated approach

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  • Miao Li
  • Dries Goossens

Abstract

This paper introduces the multi-league grouping and scheduling problem, which integrates the grouping of teams into leagues and the scheduling of each league. This involves two possibly conflicting objectives: minimizing travel distance and minimizing capacity violations of venues shared by teams. We formulate this problem as a bi-objective mixed-integer programming model. Given the NP-hardness of the grouping problem, the integrated problem is particularly challenging. Hence, we design a two-layer constructive heuristic to efficiently approximate the Pareto set, using simulated annealing on the outer layer and an integer programming model on the inner layer. We further develop a speed-up version where the inner layer is solved heuristically. We develop a series of large-scale problem instances, including one based on data from the Royal Belgian Football Association. In a computational study, we compare our algorithms with an epsilon-constraint method and evaluate their results using various multi-objective solution quality metrics.

Suggested Citation

  • Miao Li & Dries Goossens, 2025. "Grouping and scheduling multiple sports leagues: an integrated approach," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 76(4), pages 739-757, April.
    • Handle: RePEc:taf:tjorxx:v:76:y:2025:i:4:p:739-757
    DOI: 10.1080/01605682.2024.2391516
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