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Reseach Article

Use of Genetic Algorithm and Fuzzy Logic in Optimizing Graph Coloring Problem

Published on September 2016 by Tabiya Manzoor Beigh, Girdhar Gopal
Recent Innovations in Computer Science and Information Technology
Foundation of Computer Science USA
RICSIT2016 - Number 1
September 2016
Authors: Tabiya Manzoor Beigh, Girdhar Gopal
7f4bb0ed-67d8-4aa6-9f9f-c40be26d5b1c

Tabiya Manzoor Beigh, Girdhar Gopal . Use of Genetic Algorithm and Fuzzy Logic in Optimizing Graph Coloring Problem. Recent Innovations in Computer Science and Information Technology. RICSIT2016, 1 (September 2016), 1-4.

@article{
author = { Tabiya Manzoor Beigh, Girdhar Gopal },
title = { Use of Genetic Algorithm and Fuzzy Logic in Optimizing Graph Coloring Problem },
journal = { Recent Innovations in Computer Science and Information Technology },
issue_date = { September 2016 },
volume = { RICSIT2016 },
number = { 1 },
month = { September },
year = { 2016 },
issn = 0975-8887,
pages = { 1-4 },
numpages = 4,
url = { /proceedings/ricsit2016/number1/26182-2016/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 Recent Innovations in Computer Science and Information Technology
%A Tabiya Manzoor Beigh
%A Girdhar Gopal
%T Use of Genetic Algorithm and Fuzzy Logic in Optimizing Graph Coloring Problem
%J Recent Innovations in Computer Science and Information Technology
%@ 0975-8887
%V RICSIT2016
%N 1
%P 1-4
%D 2016
%I International Journal of Computer Applications
Abstract

Minimum number of colors while coloring the vertices of a graph is a massive apprehension of research scholars in the area of soft computing. Method such as Genetic Algorithm (GA) is highly preferred to solve the Graph Coloring problem by the researchers for many years. In this paper, an optimization technique based on Genetic Algorithm and Fuzzy Logic approach is applied for solving Graph Coloring Problem. The selection operator used in the optimization technique has based on Fuzzy logic. The proposed algorithm is tested on standard DIMACS instances. 11 problems from DIMACS dataset are picked and results are compared with known chromatic numbers. It has found that proposed algorithm has solved nearly all of the problem instances at very good efficiency rate.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Alpha Cut Fuzzy Logic Genetic Algorithm Graph Coloring Problem Selection