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

Aleksander Byrski; Ewelina Swiderska; Jakub Lasisz; Marek Kisiel-Dorohinicki; Tom Lenaerts; Dana Samson; Bipin Indurkhya

doi:10.7494/csci.2018.19.1.2594

Authors

Aleksander Byrski AGH University of Science and Technology
Ewelina Swiderska AGH University of Science and Technology
Jakub Lasisz AGH University of Science and Technology
Marek Kisiel-Dorohinicki AGH University of Science and Technology
Tom Lenaerts Universite Libre de Bruxelles
Dana Samson Catholique Universite de Louvain
Bipin Indurkhya Jagiellonian University

DOI:

https://doi.org/10.7494/csci.2018.19.1.2594

Abstract

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

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