Revisiting the Pheromone Evaluation Mechanism in the Interacted Multiple Ant Colonies Optimization Framework

A. Aljanaby, K.R. Ku-Mahamud, and N.M. Norwawi (Malaysia)


Ant colony optimization, combinatorial optimization problems, search stagnation, and pheromone evaluation.


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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