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Reseach Article

A Hybrid Genetic Algorithm Approach to a Departmental Class Timetabling Problem Using Efficient Data

by Arvind.S.Babu, R.Chockalingam, S.Kavitha
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 17
Year of Publication: 2010
Authors: Arvind.S.Babu, R.Chockalingam, S.Kavitha
10.5120/352-533

Arvind.S.Babu, R.Chockalingam, S.Kavitha . A Hybrid Genetic Algorithm Approach to a Departmental Class Timetabling Problem Using Efficient Data. International Journal of Computer Applications. 1, 17 ( February 2010), 99-103. DOI=10.5120/352-533

@article{ 10.5120/352-533,
author = { Arvind.S.Babu, R.Chockalingam, S.Kavitha },
title = { A Hybrid Genetic Algorithm Approach to a Departmental Class Timetabling Problem Using Efficient Data },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 17 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 99-103 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number17/352-533/ },
doi = { 10.5120/352-533 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:47:11.125339+05:30
%A Arvind.S.Babu
%A R.Chockalingam
%A S.Kavitha
%T A Hybrid Genetic Algorithm Approach to a Departmental Class Timetabling Problem Using Efficient Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 17
%P 99-103
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The application of Genetic Algorithm with a local search operation performed within its loop has provided very accurate results, but the algorithm take a lot of time to arrive at an optimal solution. This paper describes the use of a Hybrid Genetic Algorithm using efficient data structures to automate the construction of a departmental class timetable. This problem is concerned with the allocation of faculty resources to concerned student groups and their corresponding timeslots. The quality of the solution is determined in terms of a penalty value which determines the degree to which various constraints are satisfied. This algorithm is tested over established datasets and the performance of the algorithm over different datasets. The result has confirmed that this algorithm in conjuncture with efficient data structures is able to produce high quality solutions for a departmental class timetable with short span of time. It is thus concluded that organization of data plays a major role in the performance of the Hybrid Genetic Algorithm to produce high quality solutions.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Hash Hard and soft constraints Hybrid GA Local search