Genetic Algorithm for Solving Multi-Objective Optimization in Examination Timetabling Problem

Son Tung Ngo, Jafreezal B Jaafar, Izzatdin Abdul Aziz, Giang Hoang Nguyen, Anh Ngoc Bui


Examination timetabling is one of 3 critical timetabling jobs besides enrollment timetabling and teaching assignment. After a semester, scheduling examinations is not always an easy job in education management, especially for many data. The timetabling problem is an optimization and Np-hard problem. In this study, we build a multi-objective optimizer to create exam schedules for more than 2500 students. Our model aims to optimize the material costs while ensuring the dignity of the exam and students' convenience while considering the rooms' design, the time requirement of each exam, which involves rules and policy constraints. We propose a programmatic compromise to approach the maximum tar-get optimization model and solve it using the Genetic Algorithm. The results show the effectiveness of the introduced algorithm.


examination timetabling; multi-objective optimization; combinatory optimization; genetic algorithm; compromise programming

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Copyright (c) 2021 Son Tung Ngo, Giang Hoang Nguyen, Anh Ngoc Bui, JAFREEZAL B JAAFAR

International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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