Mathurin Soh ; Anderson Nguetoum Likeufack - A New Hybrid Algorithm Based on Ant Colony Optimization and Recurrent Neural Networks with Attention Mechanism for Solving the Traveling Salesman Problem

arima:13340 - Revue Africaine de Recherche en Informatique et Mathématiques Appliquées, January 28, 2025, Volume 42 - Special issue CRI 2023 - 2024 - https://doi.org/10.46298/arima.13340
A New Hybrid Algorithm Based on Ant Colony Optimization and Recurrent Neural Networks with Attention Mechanism for Solving the Traveling Salesman ProblemArticle

Authors: Mathurin Soh 1; Anderson Nguetoum Likeufack 1

  • 1 Unité de Recherche en Informatique Fondamentale, Ingénierie et Applications [Dschang]

In this paper, we propose a hybrid approach for solving the symmetric traveling salesman problem. The proposed approach combines the ant colony algorithm (ACO) with neural networks based on the attention mechanism. The idea is to use the predictive capacity of neural networks to guide the behaviour of ants in choosing the next cities to visit and to use the prediction results of the latter to update the pheromone matrix, thereby improving the quality of the solutions obtained. In concrete terms, attention is focused on the most promising cities by taking into account both distance and pheromone information thanks to the attention mechanism, which makes it possible to assign weights to each city according to its degree of relevance. These weights are then used to predict the next towns to visit for each city. Experimental results on instancesTSP from the TSPLIB library demonstrate that this hybrid approach is better compared to the classic ACO.


Volume: Volume 42 - Special issue CRI 2023 - 2024
Published on: January 28, 2025
Accepted on: January 17, 2025
Submitted on: April 3, 2024
Keywords: Traveling Salesman Problem,Recurrent Neural Networks,Hybridization,Attention Mechanism,Ant Colony Algorithm,Problème du voyageur de commerce,Réseaux de neurones récurrents,hybridation,mécanisme d'attention,algorithme de fourmis.,[SCCO.COMP]Cognitive science/Computer science

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