Publication: Revisiting the pheromone evaluation mechanism in the interacted multiple ant colonies optimization framework
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Date
2010
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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.
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Keywords
Ant colony optimization, Combinatorial optimization problems, Pheromone evaluation, Search stagnation, Ant algorithms, Ant colonies, Ant colony systems, Ant-colony optimization, Combinatorial optimization problems, Computational tests, Max-Min Ant System, Optimization framework, Algorithms, Artificial intelligence, Combinatorial optimization