@article{01J9Y5HTH8W2Q2YKQRAYRZRM11,
  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.}},
  author       = {{Li, Miao and Goossens, Dries}},
  issn         = {{0160-5682}},
  journal      = {{JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY}},
  keywords     = {{OR in sports,sport teams grouping,multi-league scheduling,round,robin,different league sizes,bi-objective optimization,MULTIOBJECTIVE OPTIMIZATION,FOOTBALL-LEAGUE,PATTERN SETS,PERFORMANCE,FEASIBILITY,ALGORITHMS,COMPLEXITY,TOURNAMENT,TEAMS}},
  language     = {{eng}},
  number       = {{4}},
  pages        = {{739--757}},
  title        = {{Grouping and scheduling multiple sports leagues : an integrated approach}},
  url          = {{http://doi.org/10.1080/01605682.2024.2391516}},
  volume       = {{76}},
  year         = {{2024}},
}

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