We describe the solver that we developed for the Sports Timetabling Competition ITC2021, a three-stage simulated annealing approach, that makes use of a portfolio of six different neighborhoods. Five of these neighborhoods are taken from the literature on round-robin tournament scheduling, whereas the last one, denoted as PartialSwapTeamsPhased, is a novel contribution and it is specifically designed for the phased version of the problem. We perform a comprehensive and statistically principled tuning procedure to find the best combination of parameters for the competition instances. We dedicate specific focus to evaluate the contribution given by the new neighborhood PartialSwapTeamsPhased, which yielded better results on most phased instances. Overall, the final outcome is that the three-stage simulated annealing solver is able to find a feasible solution on 44 out of 45 instances and ranked second in both the first competition milestone and the final round. We also propose an Integer Linear Programming model implemented in CPLEX, which, unfortunately, did not produce significant results on the instances of the competition.

我们描述了我们为体育时间表竞赛 ITC2021 开发的求解器，这是一种三阶段模拟退火方法，利用了六个不同社区的组合。其中五个邻域取自关于循环锦标赛安排的文献，而最后一个，表示为 PartialSwapTeamsPhased，是一个新颖的贡献，它是专门为该问题的阶段版本而设计的。我们执行了一个全面且有统计学原则的调整程序，以找到竞赛实例的最佳参数组合。我们专注于评估新邻域 PartialSwapTeamsPhased 的贡献，它在大多数阶段性实例上产生了更好的结果。全面的，最终结果是，三阶段模拟退火求解器能够在 45 个实例中的 44 个上找到可行的解决方案，并且在第一个比赛里程碑和最后一轮比赛中均排名第二。我们还提出了在 CPLEX 中实现的整数线性规划模型，不幸的是，该模型在竞赛实例上没有产生显着的结果。