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

Byrski A., Świderska E., Łasisz J., Kisiel-Dorohinicki M., Lenaerts T., Samson D., Indurkhya B.

Computer Science

2018

Vol. 19 (1)

81--98

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.