A Survey of Computational Intelligence in Educational Timetabling

Kaixiang Zhu,Michael Li,Lily D Li

doi:10.18178/ijmlc.2021.11.1.1012

Kaixiang Zhu, Michael Li + Show 1 more

Open Access

https://doi.org/10.18178/ijmlc.2021.11.1.1012

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Abstract

Timetabling problems have been widely studied, of which Educational Timetabling Problem (ETP) is the biggest section. Generally, ETP can be divided into three modules, namely, course timetabling, school timetabling, and examination timetabling. For solving ETP, many techniques have been developed including conventional algorithms and computational intelligence approaches. Several surveys have been conducted focusing on those methods. Some surveys target on particular categories; some tend to cover all types of approaches. However, there are lack of reviews specifically focusing on computational intelligence in ETP. Therefore, this paper aims at providing a reference of selecting a method for the applications of ETP by reviewing popular computational intelligent algorithms, such as meta-heuristics, hyper-heuristics, hybrid methods, fuzzy logic, and multi-agent systems. The application would be categorised and described into the three types of ETP respectively.

Highlights

Timetabling problem is known as an NP-complete problem, meaning that it is difficult to provide a general optimal solution for a wide range of cases
Around three thousand studies are published every year in this filed, within which university timetabling is the most popular section occupying over 85% publication volume (Fig. 1)
This paper reviewed the computational intelligence applied to educational timetabling problems

Summary

Introduction

Timetabling problem is known as an NP-complete problem, meaning that it is difficult to provide a general optimal solution for a wide range of cases. There has been a large interest in researching timetabling problems. Around three thousand studies are published every year in this filed, within which university timetabling is the most popular section occupying over 85% publication volume (Fig. 1). Since Appleby, Blake and Newman [1], which may be the first timetabling study in the computer field, computational timetabling has been developed over 50 years, and some surveys have been done to review those techniques [2]-[10]. Some surveys focused on computational intelligence, they paid attention to a single category [6]. This paper aims at reviewing the current computational intelligent approaches in ETP and giving an overview for further research in solution model construction and algorithm selection

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