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Parametric Analysis of Nature Inspired Optimization Techniques

by Yugal Kumar, Dharmender Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 32 - Number 3
Year of Publication: 2011
Authors: Yugal Kumar, Dharmender Kumar
10.5120/3888-5442

Yugal Kumar, Dharmender Kumar . Parametric Analysis of Nature Inspired Optimization Techniques. International Journal of Computer Applications. 32, 3 ( October 2011), 42-49. DOI=10.5120/3888-5442

@article{ 10.5120/3888-5442,
author = { Yugal Kumar, Dharmender Kumar },
title = { Parametric Analysis of Nature Inspired Optimization Techniques },
journal = { International Journal of Computer Applications },
issue_date = { October 2011 },
volume = { 32 },
number = { 3 },
month = { October },
year = { 2011 },
issn = { 0975-8887 },
pages = { 42-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume32/number3/3888-5442/ },
doi = { 10.5120/3888-5442 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:18:13.963100+05:30
%A Yugal Kumar
%A Dharmender Kumar
%T Parametric Analysis of Nature Inspired Optimization Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 32
%N 3
%P 42-49
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

There are large numbers of the optimization technique that have been used to optimize the thing in the field of computer science, transportation engineering, mechanical engineering, management and so on. But the traditional optimization techniques are replaced by nature inspired techniques. These technique involve directly or indirectly the participation of nature such as GA, ACO, BCO SA, SS. Such techniques provide an abstract way to solve the problem. Each technique is differing from the other technique but each technique having some similarity with other techniques. This paper provides the comparative analysis of Nature inspired optimization techniques in the tabular form.

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Index Terms

Computer Science
Information Sciences

Keywords

Optimization Techniques Stochastic Population Heuristic