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Reseach Article

University Timetabling based on Hard Constraints using Genetic Algorithm

by Sanjay R. Sutar, Rajan S. Bichkar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 42 - Number 15
Year of Publication: 2012
Authors: Sanjay R. Sutar, Rajan S. Bichkar
10.5120/5766-7964

Sanjay R. Sutar, Rajan S. Bichkar . University Timetabling based on Hard Constraints using Genetic Algorithm. International Journal of Computer Applications. 42, 15 ( March 2012), 1-7. DOI=10.5120/5766-7964

@article{ 10.5120/5766-7964,
author = { Sanjay R. Sutar, Rajan S. Bichkar },
title = { University Timetabling based on Hard Constraints using Genetic Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 42 },
number = { 15 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume42/number15/5766-7964/ },
doi = { 10.5120/5766-7964 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:31:20.494498+05:30
%A Sanjay R. Sutar
%A Rajan S. Bichkar
%T University Timetabling based on Hard Constraints using Genetic Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 42
%N 15
%P 1-7
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The proposed system presents a novel approach of solving University timetabling which is NP-hard problem using Genetic Algorithm. Genetic Algorithm is frequently deployed Meta heuristics algorithm which can be effectively used to difficult combinatorial optimization problems. Although, there has been an extensive research towards this field but majority of the research results are much in its nascent stage. The previous researchers have used various methods like Tabu search, Simulated Annealing, network flow, graph coloring, etc. Genetic Algorithms are effective in solving many such optimization problems. The current work presented uses Genetic Algorithm to design an effective model for scheduling with challenging constraints considerations. The objective of the research is to create a model using Genetic Algorithm to the extent it can be used to generate the acceptable schedule using probabilistic operators like mutation and crossover. The design of the fitness function has considered the hard constraints. The simulation shows the better result in minimum time.

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Index Terms

Computer Science
Information Sciences

Keywords

Class Scheduling Problem Cross Over Genetic Algorithm Mutation