Solving university course timetabling problems is a large and complex task. Moreover, every new academic term, a new timetable is likely to be scheduled due to disruptions (e.g., changes in teacher-lecture allocation). Nevertheless, the university infrastructure, the overall curricular plans, and the number of students/teachers is still very similar in consecutive terms. For this reason, a timetable does not need to be always scheduled from scratch since it can produce a completely different solution from the previous one, thus creating undesirable changes for many actors. This paper addresses the Minimal Perturbation Problem (MPP) in university course timetabling. Given a set of disruptions that make a timetable no longer feasible, a solution to the MPP is the closest new feasible timetable with respect to the original timetable. We propose and analyze two different integer programming models to encode the MPP. To validate the proposed models, disruptions are randomly generated based on the probability distributions learned from the history of timetables over the last five years in the Instituto Superior Tecnico (IST) the engineering school from Universidade de Lisboa. Overall, our models, combined with an incremental approach, are shown to be able to efficiently solve all problem instances.

中文翻译：

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时间表的中断：里斯本大学的案例研究

解决大学课程安排问题是一项庞大而复杂的任务。此外，由于中断（例如，教师讲座分配的变化），每一个新学期，都可能安排新的时间表。尽管如此，大学的基础设施、整体课程计划和学生/教师的数量仍然非常相似。出于这个原因，时间表不需要总是从头开始安排，因为它可以产生与前一个完全不同的解决方案，从而对许多参与者造成不受欢迎的变化。本文解决了大学课程时间表中的最小扰动问题 (MPP)。给定一组使时间表不再可行的中断，MPP 的解决方案是与原始时间表最接近的新可行时间表。我们提出并分析了两种不同的整数规划模型来编码 MPP。为了验证所提出的模型，根据从里斯本大学工程学院过去五年的时间表历史中学到的概率分布随机生成中断。总的来说，我们的模型与增量方法相结合，能够有效地解决所有问题实例。