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Title: Revisiting the pheromone evaluation mechanism in the interacted multiple ant colonies optimization framework
Authors: A., Aljanaby,
K.R., Ku-Mahamud,
N.Md., Norwawi,
Keywords: Ant colony optimization
Combinatorial optimization problems
Pheromone evaluation
Search stagnation
Issue Date: 2010
Abstract: Interacted Multiple Ant Colonies Optimization (IMACO) is a newly proposed framework. Pheromone evaluation mechanism is playing a central role in this framework. This paper describes the newly proposed IMACO framework and proposes a more effective pheromone evaluation mechanism. Computational tests show that the new pheromone evaluation mechanism 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.
ISBN: 9780-8898-6818-2
Appears in Collections:Proceedings of the 10th IASTED International Conference on Artificial Intelligence and Applications, AIA 2010

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