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Using Nested Tables and Mutation in Genetic Algorithms (NTMGA) to Solve Timetabling Problem in Object-Relational Model

by Ahmed Sultan Al-hegami, Wadee Al-qubati, Ammar Zahary
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 9
Year of Publication: 2012
Authors: Ahmed Sultan Al-hegami, Wadee Al-qubati, Ammar Zahary
10.5120/8595-2355

Ahmed Sultan Al-hegami, Wadee Al-qubati, Ammar Zahary . Using Nested Tables and Mutation in Genetic Algorithms (NTMGA) to Solve Timetabling Problem in Object-Relational Model. International Journal of Computer Applications. 54, 9 ( September 2012), 25-30. DOI=10.5120/8595-2355

@article{ 10.5120/8595-2355,
author = { Ahmed Sultan Al-hegami, Wadee Al-qubati, Ammar Zahary },
title = { Using Nested Tables and Mutation in Genetic Algorithms (NTMGA) to Solve Timetabling Problem in Object-Relational Model },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 9 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 25-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number9/8595-2355/ },
doi = { 10.5120/8595-2355 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:55:16.062287+05:30
%A Ahmed Sultan Al-hegami
%A Wadee Al-qubati
%A Ammar Zahary
%T Using Nested Tables and Mutation in Genetic Algorithms (NTMGA) to Solve Timetabling Problem in Object-Relational Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 9
%P 25-30
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, the nested tables feature in relational- object database is applied along with the feature of Mutation in Genetic Algorithms (GA) to solve the problem of timetabling, especially coursework timetables. The advantage of using nested tables is utilized to cancel a lot of conflicts and improve the operations of the Mutation in GA for the ideal solutions of multi-fewest number of generations and a short time has been concluded infer. Our approach conducted by this paper which is called NTMGA has been implemented and applied to timetable problem of Computer Science Department at the University of Science and Technology (UST). Results proved a satisfactory performance of NTMGA approach in terms of the absence of conflicts and a fast release of schedules has been obtained.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Genetic Algorithm (GA) NTMGA Timetabling Chromosome Fitness Mutation object relational model nested tables

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