Article

Application of genetic algorithm for solving university timetabling problems: a case study of Thai universities

Authors:

Nawat Nuntasen,

Supachate InnetAuthors Info & Claims

SMO'07: Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization

Pages 128 - 133

Published: 15 September 2007 Publication History

Abstract

There are many problems in university timetabling derived from various limitations and constraints. They comprise congruence and relation among group of students, subjects, lecturers, rooms, periods and time space. Genetic Algorithm (GA) was applied to deal with these problems. This paper shows the innovation of GA operator in level of elements. Fitness functions of chromosomes, GA operators (crossover and mutation) are run through the process of this development. Appropriate value testing to search for the most effective point was conducted under variation of proportion between crossover and mutation. The result of this research displayed that the given appropriate value of crossover 93% and mutation 7% of GA operator is the best rate to resolve the problem of university timetabling.

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Nuntasen NInnet S(2007)A novel approach of genetic algorithm for solving university timetabling problemsProceedings of the 7th Conference on 7th WSEAS International Conference on Applied Computer Science - Volume 710.5555/1348171.1348214(246-252)Online publication date: 21-Nov-2007
https://dl.acm.org/doi/10.5555/1348171.1348214

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Published In

SMO'07: Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization

September 2007

523 pages

ISBN:9789606766077

Editor:
De Xu
Beijijng Jiaotong University, China

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Stevens Point, Wisconsin, United States

Publication History

Published: 15 September 2007

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Nuntasen NInnet S(2007)A novel approach of genetic algorithm for solving university timetabling problemsProceedings of the 7th Conference on 7th WSEAS International Conference on Applied Computer Science - Volume 710.5555/1348171.1348214(246-252)Online publication date: 21-Nov-2007
https://dl.acm.org/doi/10.5555/1348171.1348214

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A novel approach of genetic algorithm for solving university timetabling problems: a case study of Thai universities

An improved genetic algorithm with conditional genetic operators and its application to set-covering problem

Solving Japanese nonograms by Taguchi-based genetic algorithm

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