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A GA based Approach to Find Minimal Vertex Cover

Published on May 2014 by Udit Kr. Chakraborty, Debanjan Konar, Chandralika Chakraborty
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National Conference cum Workshop on Bioinformatics and Computational Biology
Foundation of Computer Science USA
NCWBCB - Number 3
May 2014
Authors: Udit Kr. Chakraborty, Debanjan Konar, Chandralika Chakraborty
a81c8d64-25ef-43d3-84f3-b034ed6acdf4

Udit Kr. Chakraborty, Debanjan Konar, Chandralika Chakraborty . A GA based Approach to Find Minimal Vertex Cover. National Conference cum Workshop on Bioinformatics and Computational Biology. NCWBCB, 3 (May 2014), 5-7.

@article{
author = { Udit Kr. Chakraborty, Debanjan Konar, Chandralika Chakraborty },
title = { A GA based Approach to Find Minimal Vertex Cover },
journal = { National Conference cum Workshop on Bioinformatics and Computational Biology },
issue_date = { May 2014 },
volume = { NCWBCB },
number = { 3 },
month = { May },
year = { 2014 },
issn = 0975-8887,
pages = { 5-7 },
numpages = 3,
url = { /proceedings/ncwbcb/number3/16520-1421/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference cum Workshop on Bioinformatics and Computational Biology
%A Udit Kr. Chakraborty
%A Debanjan Konar
%A Chandralika Chakraborty
%T A GA based Approach to Find Minimal Vertex Cover
%J National Conference cum Workshop on Bioinformatics and Computational Biology
%@ 0975-8887
%V NCWBCB
%N 3
%P 5-7
%D 2014
%I International Journal of Computer Applications
Abstract

Genetic Algorithms are a class of Optimization Techniques which has been developed under inspiration of the Darwinian Theory of Survival of the Fittest. This technique has been successfully used to solve many optimization problems which otherwise pose huge challenges for computation. This paper presents a GA based approach to solve the Minimal Vertex Cover problem of Graph Theory.

References
  1. Samir Roy, Udit Chakraborty, Introduction to Soft Computing – Neuro-Fuzzy and Genetic Algorithms, Pearson Education, 2013.
  2. J. -M. Renders, H. Bersini, "Hybridizing genetic algorithms with hill-climbing methods for global optimization: two possible ways", Proceedings of the First IEEE Conference on Evolutionary Computation, vol. 1 (1994), 312,317.
  3. I. Dinur and S. Safra, "On the hardness of approximating minimum vertex cover", Annals of Mathematics, 162 (2005), 439–485.
  4. C. Papadimitriou and M. Yannakakis, "Optimization, approximation and complexity classes", Journal of Computer and System Sciences 43 (1991), 424–440.
  5. P. S. Oliveto, J. He and X. Yao, "Evolutionary Algorithms and the Vertex Cover Problem", IEEE Congress on Evolutionary Computation (2007), 1870-1877.
  6. S. Khuri and T. Black, "An evolutionary heuristic for the minimum vertex cover problem", in Genetic Algorithms within the Framework of Evolutionary Computation- Proceedings of the KI-94 Workshop, J. Hopf, Ed. , Saarbrucken, Germany, 1994, pp. 86-90Forman, G. 2003. An extensive empirical study of feature selection metrics for text classification. J. Mach. Learn. Res. 3 (Mar. 2003), 1289-1305.
  7. K. S. Christos. H. Papadimitriou, CombinatorialOptimization: Algorithms and Complexity, Dover Publications Inc. , 1982.
Index Terms

Computer Science
Information Sciences

Keywords

Minimal Vertex Cover Genetic-algorithms Chromosomes Mutation Generations.