The behaviour of ACS-TSP algorithm when adapting both pheromone parameters using fuzzy logic controller

Safae Bouzbita, Abdellatif El Afia, Rdouan Faizi


In this paper, an evolved ant colony system (ACS) is proposed by dynamically adapting the responsible parameters for the decay of the pheromone trails πœ‰ and 𝜌 using fuzzy logic controller (FLC) applied in the travelling salesman problems (TSP). The purpose of the proposed method is to understand the effect of both parameters πœ‰ and 𝜌 on the performance of the ACS at the level of solution quality and convergence speed towards the best solutions through studying the behavior of the ACS algorithm during this adaptation. The adaptive ACS is compared with the standard one. Computational results show that the adaptive ACS with dynamic adaptation of local pheromone parameter πœ‰ is more effective compared to the standard ACS.


Ant colony system ; Dynamic parameter adaptation fuzzy logic controller; Swarm intelligence; Machine learning

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578

This journal is published by theΒ Institute of Advanced Engineering and Science (IAES)Β in collaboration withΒ Intelektual Pustaka Media Utama (IPMU).