Emergence of population structure in socio-cognitively inspired Ant Colony Optimization

Byrski, Aleksander;Swiderska, Ewelina;Lasisz, Jakub;Kisiel-Dorohinicki, Marek;Indurkhya, Bipin;et.al.
(2018) Computer Science — Vol. 19, n° 1, p. 83-99 (2018)

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Authors
  • Byrski, AleksanderAGH University of Science and Technology, Poland
    Author
  • Swiderska, EwelinaAGH University of Science and Technology, Poland
    Author
  • Lasisz, JakubAGH University of Science and Technology, Poland
    Author
  • Kisiel-Dorohinicki, MarekAGH University of Science and Technology, Poland
    Author
  • Samson, DanaUCLouvain
    Author
  • Indurkhya, BipinJagiellonian University, Poland
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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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Byrski, A., Swiderska, E., Lasisz, J., Kisiel-Dorohinicki, M., Lenaerts, T., Samson, D., & Indurkhya, B. (2018). Emergence of population structure in socio-cognitively inspired Ant Colony Optimization. Computer Science, 19(1), 83-99. https://doi.org/10.7494/csci.2018.19.1.2594 (Original work published 2018)