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An Experimental Study of the Search Stagnation in Ants Algorithms

by Alaa Aljanaby
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 148 - Number 14
Year of Publication: 2016
Authors: Alaa Aljanaby
10.5120/ijca2016910861

Alaa Aljanaby . An Experimental Study of the Search Stagnation in Ants Algorithms. International Journal of Computer Applications. 148, 14 ( Aug 2016), 1-4. DOI=10.5120/ijca2016910861

@article{ 10.5120/ijca2016910861,
author = { Alaa Aljanaby },
title = { An Experimental Study of the Search Stagnation in Ants Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2016 },
volume = { 148 },
number = { 14 },
month = { Aug },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume148/number14/25837-2016910861/ },
doi = { 10.5120/ijca2016910861 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:53:20.400118+05:30
%A Alaa Aljanaby
%T An Experimental Study of the Search Stagnation in Ants Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 148
%N 14
%P 1-4
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper conducts experimental tests to study the stagnation behavior the Interacted Multiple Ant Colonies Optimization (IMACO) framework. The idea of different ant colonies use different types of problem dependent heuristics has been proposed as well. The performance of IMACO was demonstrated by comparing it with the Ant Colony System (ACS) the best performing ant algorithm. The computational results show the dominance of IMACO and that IMACO suffers less from stagnation than ACS.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Ant colony optimization combinatorial optimization problems search stagnation.

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