Educational timetabling is an ongoing challenging administrative task that is required in most academic institutions. This is mainly due to a large number of constraints and requirements that have to be satisfied. Educational timetabling problems have been classified as NP-hard problems and can be divided into three types: exam timetabling, course timetabling and high school timetabling. The domain of high school timetabling is not well developed when compared to other fields of educational timetabling such as university exam timetabling and course timetabling. As the evolution of the educational systems are continuous, new challenges often arise, requiring new models and solution methodologies. Over the years, a number of methodologies have been developed to address high school timetabling problems. However, there are no comparative studies or rigorous analysis of these methodologies. This survey paper aims to provide a scientific review of high school timetabling. The paper presents a categorisation of the methodologies conducted in recent years based on chronology, category and application (dataset). We first present comparative studies on the success of proposed methodologies. The components and mechanisms of different methodologies are analysed and compared. We also discuss their performance, advantages, disadvantages and potential for improvement. Methodology wise, a shift of popularity from meta-heuristic to mathematical optimisation is observed in recent years. Another observation is that more researchers are opting for XHSTT formatted datasets as a testbed for their algorithms. Finally, we outline the industrial perspective, trends and future direction in high school timetabling optimisation problems.

教育时间表是大多数学术机构都需要进行的一项具有挑战性的持续管理任务。这主要是由于必须满足大量约束和要求。教育时间表问题已被归类为NP难题，可以分为三种类型：考试时间表，课程时间表和高中时间表。与其他教育时间表领域（例如大学考试时间表和课程时间表）相比，高中时间表的领域尚不完善。随着教育系统的不断发展，经常会出现新的挑战，需要新的模型和解决方法。多年来，已经开发出许多方法来解决高中课程时间表问题。然而，这些方法没有比较研究或严格分析。本调查报告旨在对高中课程时间表进行科学审查。本文介绍了根据年代，类别和应用（数据集）对近年来进行的方法进行的分类。我们首先介绍对拟议方法成功与否的比较研究。分析和比较了不同方法的组成部分和机制。我们还将讨论它们的性能，优点，缺点和改进的潜力。从方法论的角度来看，近年来发现流行度已从元启发式优化转向数学优化。另一个观察结果是，越来越多的研究人员选择XHSTT格式的数据集作为其算法的测试平台。最后，我们概述了产业前景，