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

Tung, S.N. and Jaafar, J.B. and Aziz, I.A. and Nguyen, H.G. and Bui, A.N. (2021) Genetic Algorithm for Solving Multi-Objective Optimization in Examination Timetabling Problem. International Journal of Emerging Technologies in Learning, 16 (11). pp. 4-24.

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Abstract

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 design of the rooms, the time requirement of each exam, which involves rules and policy constraints. We propose a programmatic compromise to approach the maximum target optimization model and solve it using the Genetic Algorithm. The results show the effective of the introduced algorithm. © 2021. All rights reserved

Item Type:Article
Impact Factor:cited By 0
Uncontrolled Keywords:Education computing; Job shop scheduling; Multiobjective optimization; NP-hard; Scheduling, Algorithm for solving; Education management; Examination timetabling; Multi objective; Policy constraints; Target optimization; Time requirements; Timetabling problem, Genetic algorithms
ID Code:23735
Deposited By: Ms Sharifah Fahimah Saiyed Yeop
Deposited On:19 Aug 2021 09:40
Last Modified:19 Aug 2021 09:40

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