In this paper, we present our solver for the new variant of the University Timetabling Problem, which was introduced in the framework of Fourth International Timetabling Competition (ITC2019). This problem is defined on top of previous course timetabling problems in the literature, but introduces several new elements, both in terms of new features like student sectioning and new required and optional elements like distribution constraints. Our approach for solving this problem is based on the simulated annealing metaheuristic and consists of two phases. The first phase focuses on finding a feasible solution, and the second phase attempts to optimize the final score while keeping the solution feasible. Our solver detects local optima and applies gradual penalization to force solutions to new neighborhoods. The solver also detects required constraints which are difficult to satisfy and performs a specialized search on them. These adaptively applied mechanisms allow the solver to find feasible solutions for all problem instances of the competition. Results show that our solver gives good overall results and is competitive against other approaches presented in ITC2019.

在本文中，我们介绍了在第四届国际时间表竞赛 (ITC2019) 框架中引入的大学时间表问题的新变体的求解器。这个问题是在文献中先前课程时间表问题的基础上定义的，但引入了几个新元素，包括学生分区等新功能以及分布约束等新的必需和可选元素。我们解决这个问题的方法是基于模拟退火元启发式算法，包括两个阶段。第一阶段侧重于寻找可行的解决方案，第二阶段尝试在保持解决方案可行的同时优化最终得分。我们的求解器检测局部最优并应用渐进惩罚来强制解决新社区。求解器还检测难以满足的所需约束并对它们执行专门的搜索。这些自适应应用的机制允许求解器为竞赛的所有问题实例找到可行的解决方案。结果表明，我们的求解器提供了良好的整体结果，并且与 ITC2019 中提出的其他方法相比具有竞争力。