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

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)81-98
Number of pages18
JournalComputer Science
Volume19
Issue number1
DOIs
Publication statusPublished - 2018

Keywords

  • Ant colony optimization
  • Discrete optimization
  • Emergence
  • Socio-cognitive systems

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