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Solving Timetabling problems using Genetic Algorithm Technique

by H. M. Sani, M. M. Yabo
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 134 - Number 15
Year of Publication: 2016
Authors: H. M. Sani, M. M. Yabo
10.5120/ijca2016907960

H. M. Sani, M. M. Yabo . Solving Timetabling problems using Genetic Algorithm Technique. International Journal of Computer Applications. 134, 15 ( January 2016), 33-38. DOI=10.5120/ijca2016907960

@article{ 10.5120/ijca2016907960,
author = { H. M. Sani, M. M. Yabo },
title = { Solving Timetabling problems using Genetic Algorithm Technique },
journal = { International Journal of Computer Applications },
issue_date = { January 2016 },
volume = { 134 },
number = { 15 },
month = { January },
year = { 2016 },
issn = { 0975-8887 },
pages = { 33-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume134/number15/23994-2016907960/ },
doi = { 10.5120/ijca2016907960 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:34:26.529391+05:30
%A H. M. Sani
%A M. M. Yabo
%T Solving Timetabling problems using Genetic Algorithm Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 134
%N 15
%P 33-38
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The timetabling problem is always a difficult task which comes up every calendar year in educational institutions. More especially if it has to be done manually. Various institutions of learning across the country are being faced with a lot of difficulties preparing examination timetable. Most of this problems are usually attributed to the constant increase in the number of students and courses while having limited resources (exam classes) to use in scheduling. The aim of this paper is to propose the use of genetic algorithm technique to develop an easier, effective and efficient timetable using in order to ease the problems faced during scheduling of examination. Although, there are various scheduling techniques, but the use of Genetic Algorithm was based on the fact that, the algorithm are robust there by properly fits into complex problem space. The new method is aimed at providing a more flexible timetable representation and proved to be efficient in real life applications..

References
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Index Terms

Computer Science
Information Sciences

Keywords

Timetable scheduling Genetic Algorithm Constraints