DocumentCode
3517456
Title
An Exploration Technique for the Interacted Multiple Ant Colonies Optimization Framework
Author
Aljanaby, Alaa ; Ku-Mahamud, Ku Ruhana ; Norwawi, Norita Md
Author_Institution
Coll. of Arts & Sci., Univ. Utara Malaysia, Sintok, Malaysia
fYear
2010
fDate
27-29 Jan. 2010
Firstpage
92
Lastpage
95
Abstract
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.
Keywords
minimax techniques; ant colony system; exploration technique; interacted multiple ant colonies optimization framework; max-min ant system; optimization problem; search space; Ant colony optimization; Art; Artificial intelligence; Educational institutions; Insects; Intelligent systems; Particle swarm optimization; Routing; System testing; Traveling salesman problems; ant colony optimization; combinatorial optimization problems; exploitation; exploration; search stagnation;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems, Modelling and Simulation (ISMS), 2010 International Conference on
Conference_Location
Liverpool
Print_ISBN
978-1-4244-5984-1
Type
conf
DOI
10.1109/ISMS.2010.28
Filename
5416116
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