Academy & Industry Research Collaboration Center (AIRCC)

Volume 10, Number 17, December 2020

Genetic Algorithm for Exam Timetabling Problem - A Specific Case for
Japanese University Final Presentation Timetabling


Jiawei LI and Tad Gonsalves, Sophia University, Japan


This paper presents a Genetic Algorithm approach to solve a specific examination timetabling problem which is common in Japanese Universities. The model is programmed in Excel VBA programming language, which can be run on the Microsoft Office Excel worksheets directly. The model uses direct chromosome representation. To satisfy hard and soft constraints, constraint-based initialization operation, constraint-based crossover operation and penalty points system are implemented. To further improve the result quality of the algorithm, this paper designed an improvement called initial population pre-training. The proposed model was tested by the real data from Sophia University, Tokyo, Japan. The model shows acceptable results, and the comparison of results proves that the initial population pre-training approach can improve the result quality.


Examination timetabling problem, Excel VBA, Direct chromosome representation, Genetic Algorithm Improvement.