An exploration technique for the interacted multiple ant colonies optimization framework

Interacted Multiple Ant Colonies Optimization (IMACO) is a newly proposed framework. In this framework several colonies of artificial ants are utilized. These colonies are working cooperatively to solve an optimization problem using some interaction technique. Exploration technique is doing an essen...

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Main Authors: A., Aljanaby, K.R., Ku-Mahamud, N.Md., Norwawi
Format: Conference Paper
Language:en_US
Published: 2015
Subjects:
Online Access:http://ddms.usim.edu.my/handle/123456789/9032
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Institution: Universiti Sains Islam Malaysia
Language: en_US
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spelling my.usim-90322015-08-12T02:35:41Z An exploration technique for the interacted multiple ant colonies optimization framework A., Aljanaby, K.R., Ku-Mahamud, N.Md., Norwawi, Ant colony optimization Combinatorial optimization problems Exploitation Exploration Search stagnation Interacted Multiple Ant Colonies Optimization (IMACO) is a newly proposed framework. In this framework several colonies of artificial ants are utilized. These colonies are working cooperatively to solve an optimization problem using some interaction technique. Exploration technique is doing an essential job in this framework. This technique is responsible for directing the activity of utilized colonies towards the different parts of the huge search space. This paper describes the newly proposed IMACO framework and proposes an effective exploration technique. Computational tests show that the new exploration technique can furthermore improve the IMACO performance. These tests also show the capability of IMACO to outperform other well known ant algorithms like ant colony system and max-min ant system. © 2010 IEEE. 2015-08-12T02:35:41Z 2015-08-12T02:35:41Z 2010 Conference Paper 9780-7695-3973-7 http://ddms.usim.edu.my/handle/123456789/9032 en_US
institution Universiti Sains Islam Malaysia
building USIM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universit Sains Islam i Malaysia
content_source USIM Institutional Repository
url_provider http://ddms.usim.edu.my/
language en_US
topic Ant colony optimization
Combinatorial optimization problems
Exploitation
Exploration
Search stagnation
spellingShingle Ant colony optimization
Combinatorial optimization problems
Exploitation
Exploration
Search stagnation
A., Aljanaby,
K.R., Ku-Mahamud,
N.Md., Norwawi,
An exploration technique for the interacted multiple ant colonies optimization framework
description Interacted Multiple Ant Colonies Optimization (IMACO) is a newly proposed framework. In this framework several colonies of artificial ants are utilized. These colonies are working cooperatively to solve an optimization problem using some interaction technique. Exploration technique is doing an essential job in this framework. This technique is responsible for directing the activity of utilized colonies towards the different parts of the huge search space. This paper describes the newly proposed IMACO framework and proposes an effective exploration technique. Computational tests show that the new exploration technique can furthermore improve the IMACO performance. These tests also show the capability of IMACO to outperform other well known ant algorithms like ant colony system and max-min ant system. © 2010 IEEE.
format Conference Paper
author A., Aljanaby,
K.R., Ku-Mahamud,
N.Md., Norwawi,
author_facet A., Aljanaby,
K.R., Ku-Mahamud,
N.Md., Norwawi,
author_sort A., Aljanaby,
title An exploration technique for the interacted multiple ant colonies optimization framework
title_short An exploration technique for the interacted multiple ant colonies optimization framework
title_full An exploration technique for the interacted multiple ant colonies optimization framework
title_fullStr An exploration technique for the interacted multiple ant colonies optimization framework
title_full_unstemmed An exploration technique for the interacted multiple ant colonies optimization framework
title_sort exploration technique for the interacted multiple ant colonies optimization framework
publishDate 2015
url http://ddms.usim.edu.my/handle/123456789/9032
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