A survey of the state-of-the-art of optimisation methodologies in school timetabling problems

2021
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.
EXPERT SYSTEMS WITH APPLICATIONS
卷号:165
ISSN:0957-4174
收录类型
SSCI
发表日期
2021
学科领域
循证管理学
国家
马来西亚
语种
英语
DOI
10.1016/j.eswa.2020.113943
其他关键词
SIMULATED ANNEALING ALGORITHM; COLUMN GENERATION APPROACH; LOCAL SEARCH ALGORITHMS; NEIGHBORHOOD SEARCH; SELECTION; MODELS
EISSN
1873-6793
被引频次(WOS)
5
被引更新日期
2022-01
来源机构
University of Nottingham Malaysia University of Nottingham La Trobe University
关键词
School timetabling Educational timetabling Meta-heuristic algorithms