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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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 |
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Ant colony optimization Combinatorial optimization problems Exploitation Exploration Search stagnation |
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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 |
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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 |
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2015 |
url |
http://ddms.usim.edu.my/handle/123456789/9032 |
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1645152523487543296 |