Abstract University Course Timetabling Problem (UCTP) is one of the most studied timetabling problems. In this work, the problem of finding a feasible solution for the UCTP, i.e., a solution that satisfies all hard constraints, is addressed. To cater for the algorithm design, the problem is firstly reformulated into a version where only one hard constraint needs to be considered in the minimization procedure. Then a novel Tabu search algorithm is proposed, which integrates the controlled randomization strategy and threshold mechanism into the original Tabu search framework. Experiments on a set of 60 well-known Lewis benchmark instances show that the proposed algorithm achieves competitive results compared with eight reference algorithms. In particular, when the stop condition is relaxed, the proposed algorithm can find feasible solutions for all the 60 instances, two of which are missed in previous study.

中文翻译：

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一种具有受控随机化的禁忌搜索算法，用于构建可行的大学课程时间表

摘要 大学课程时间表问题（UCTP）是研究最多的时间表问题之一。在这项工作中，解决了为 UCTP 寻找可行解决方案的问题，即满足所有硬约束的解决方案。为了迎合算法设计，问题首先被重新表述为在最小化过程中只需要考虑一个硬约束的版本。然后提出了一种新的禁忌搜索算法，将受控随机化策略和阈值机制集成到原始禁忌搜索框架中。在一组 60 个著名的 Lewis 基准实例上的实验表明，与八种参考算法相比，所提出的算法取得了有竞争力的结果。特别是当停止条件放宽时，