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Cluster Integrated Updation Strategies for ACO Algorithms

by Raghavendra G S, Prasanna Kumar N
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 30 - Number 2
Year of Publication: 2011
Authors: Raghavendra G S, Prasanna Kumar N
10.5120/3615-5033

Raghavendra G S, Prasanna Kumar N . Cluster Integrated Updation Strategies for ACO Algorithms. International Journal of Computer Applications. 30, 2 ( September 2011), 18-24. DOI=10.5120/3615-5033

@article{ 10.5120/3615-5033,
author = { Raghavendra G S, Prasanna Kumar N },
title = { Cluster Integrated Updation Strategies for ACO Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { September 2011 },
volume = { 30 },
number = { 2 },
month = { September },
year = { 2011 },
issn = { 0975-8887 },
pages = { 18-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume30/number2/3615-5033/ },
doi = { 10.5120/3615-5033 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:15:53.670951+05:30
%A Raghavendra G S
%A Prasanna Kumar N
%T Cluster Integrated Updation Strategies for ACO Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 30
%N 2
%P 18-24
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Ant Colony Optimization (ACO) algorithm has evolved as the most popular way to attack the combinatorial problems. The ACO algorithm employs multi agents called ants that are capable of finding optimal solution for a given problem instances. These ants at each step of the computation make probabilistic choices to include good solution component in partially constructed solution, so that better solution can be obtained in the search process. The ant algorithms are typically characterized by co-operation among the ants, greedy, heuristics and feedback approaches that helps them to achieve their goals. In this paper, we propose new updation mechanism based on clustering techniques, which is aimed at exploring the nearby solutions region. We also report in detail the impact on performance due to integration of cluster and ACO.

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Index Terms

Computer Science
Information Sciences

Keywords

Ant Combinatorial Optimization Greedy Cluster

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