A survey of the state-of-the-art of optimisation methodologies in school timetabling problems. (1st March 2021)

• Record Type: Journal Article
• Authors: Tan, Joo Siang; Goh, Say Leng; Kendall, Graham; Sabar, Nasser R.
• Is Part Of: Expert systems with applications. Volume 165(2021)
• Publication Date: 2021-03-01
• Subjects: School timetabling -- Educational timetabling -- Meta-heuristic algorithms; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2020.113943
• Languages: English
• ISSNs: 0957-4174

Abstract

Abstract: 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. Highlights: A survey of methodologies applied to school timetabling problems. A classification framework for the methodologies conducted in recent years. A model to categorise existing dataset types and their features. Outline the industry perspective, trends, and future direction.