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Emergence of population structure in socio-cognitively inspired ant colony optimization

par Byrski, Aleksander;Świderska, Ewelina;Łasisz, Jakub;Kisiel-Dorohinicki, Marek;Lenaerts, Tom ;Samson, Dana;Indurkhya, Bipin
Référence Computer Science, 19, 1, page (81-98)
Publication Publié, 2018

Article révisé par les pairs

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Résumé :

A metaheuristic proposed by us recently, Ant Colony Optimization (ACO) hybridized with socio-cognitive inspirations, turned out to generate interesting results when compared to classic ACO. Even though it does not always find better solutions to the considered problems, it usually finds sub-optimal solutions. Moreover, instead of a trial-and-error approach to configure the parameters of the ant species in the population, the actual structure of the population emerges from a predefined species-to-species ant migration strategies in our approach. Experimental results of our approach are compared to classic ACO and selected socio-cognitive versions of this algorithm.