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An Improved Function Optimization Problem (IFOP) of Evolutionary Programming Algorithm ñ A Survival Paper

by R. Karthick, S. Saravanan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 39 - Number 12
Year of Publication: 2012
Authors: R. Karthick, S. Saravanan
10.5120/4873-7302

R. Karthick, S. Saravanan . An Improved Function Optimization Problem (IFOP) of Evolutionary Programming Algorithm ñ A Survival Paper. International Journal of Computer Applications. 39, 12 ( February 2012), 25-28. DOI=10.5120/4873-7302

@article{ 10.5120/4873-7302,
author = { R. Karthick, S. Saravanan },
title = { An Improved Function Optimization Problem (IFOP) of Evolutionary Programming Algorithm ñ A Survival Paper },
journal = { International Journal of Computer Applications },
issue_date = { February 2012 },
volume = { 39 },
number = { 12 },
month = { February },
year = { 2012 },
issn = { 0975-8887 },
pages = { 25-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume39/number12/4873-7302/ },
doi = { 10.5120/4873-7302 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:26:18.153460+05:30
%A R. Karthick
%A S. Saravanan
%T An Improved Function Optimization Problem (IFOP) of Evolutionary Programming Algorithm ñ A Survival Paper
%J International Journal of Computer Applications
%@ 0975-8887
%V 39
%N 12
%P 25-28
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Evolutionary Algorithms are based on some influential principles like Survival of the Fittest and with some natural phenomena in Genetic Inheritance. The key for searching the solution in improved function optimization problems are based only on Selection and Mutation operators. This paper reflects on Survival selection schemes specifically like Truncate Selection, Proportionate Selection, Tournament Selection and Ranking Based Selection. In this paper we calculate the best fittest value among the populations which is generated.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Evolutionary Programming Function Optimization

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