Szczegóły publikacji
Opis bibliograficzny
Emergence of population structure in socio-cognitively inspired ant colony optimization / Aleksander BYRSKI, Ewelina Świderska, Jakub Łasisz, Marek KISIEL-DOROHINICKI, Tom Lenaerts, Dana Samson, Bipin Indurkhya // Computer Science ; ISSN 1508-2806. — 2018 — vol. 19 no. 1, s. 81–98. — Bibliogr. s. 97–99, Abstr.
Autorzy (7)
- AGHByrski Aleksander
- AGHŚwiderska Ewelina
- AGHŁasisz Jakub
- AGHKisiel-Dorohinicki Marek
- Lenaerts Tom
- Samson Dana
- Indurkhya Bipin
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 112816 |
|---|---|
| Data dodania do BaDAP | 2018-04-04 |
| Tekst źródłowy | URL |
| DOI | 10.7494/csci.2018.19.1.2594 |
| Rok publikacji | 2018 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Computer Science |
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.
