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Title: An exploration technique for the interacted multiple ant colonies optimization framework
Authors: A., Aljanaby,
K.R., Ku-Mahamud,
N.Md., Norwawi,
Keywords: Ant colony optimization
Combinatorial optimization problems
Search stagnation
Issue Date: 2010
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. © 2010 IEEE.
ISBN: 9780-7695-3973-7
Appears in Collections:ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation

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