Genetic Algorithm for Solving Multi-Objective Optimization in Examination Timetabling Problem
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....
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| Main Authors: | , , , , |
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| Format: | Article |
| Published: |
International Association of Online Engineering
2021
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108533046&doi=10.3991%2fijet.v16i11.21017&partnerID=40&md5=3c2e0cdd6633e224fd102ef24676c064 http://eprints.utp.edu.my/29516/ |
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| Institution: | Universiti Teknologi Petronas |
| Summary: | 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 |
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