Szczegóły publikacji
Opis bibliograficzny
Population diversity in ant-inspired optimization algorithms / Aleksander BYRSKI, Krzysztof Węgrzyński, Wojciech Radwański, Grażyna STARZEC, Mateusz STARZEC, Monika BARGIEŁ, Aleksandra URBAŃCZYK, Marek KISIEL-DOROHINICKI // Computer Science ; ISSN 1508-2806. — 2021 — vol. 22 iss. 3, s. 299-322. — Bibliogr. s. 320-322, Abstr.
Autorzy (8)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 137630 |
|---|---|
| Data dodania do BaDAP | 2021-11-29 |
| Tekst źródłowy | URL |
| DOI | 10.7494/csci.2021.22.3.4301 |
| Rok publikacji | 2021 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Computer Science |
Abstract
Measuring the diversity in evolutionary algorithms that work in real-value search spaces is often computationally complex, but it is feasible; however, measuring the diversity in combinatorial domains is practically impossible. Nevertheless, in this paper we propose several practical and feasible diversity-measurement techniques that are dedicated to ant colony optimization algorithms, leveraging the fact that we can focus on a pheromone table even though an analysis of the search space is at least an NP problem where the direct outcomes of the search are expressed and can be analyzed. Besides sketching out the algorithms, we apply them to several benchmark problems and discuss their efficacy.