Szczegóły publikacji
Opis bibliograficzny
Ant colony optimization using two-dimensional pheromone for single-objective transport problems / Grażyna STARZEC, Mateusz STARZEC, Leszek RUTKOWSKI, Marek KISIEL-DOROHINICKI, Aleksander BYRSKI // Journal of Computational Science ; ISSN 1877-7503. — 2024 — vol. 79 art. no. 102308, s. 1–9. — Bibliogr. s. 8–9, Abstr. — Publikacja dostępna online od: 2024-05-07. — L. Rutkowski - dod. afiliacja: Systems Research Institute, Polish Academy of Sciences, Warsaw
Autorzy (5)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 153325 |
|---|---|
| Data dodania do BaDAP | 2024-07-30 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.jocs.2024.102308 |
| Rok publikacji | 2024 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Journal of Computational Science |
Abstract
One of the acclaimed algorithms that is used to solve combinatorial graph problems is ant colony optimization (ACO). In this article, we focus on a novel extended model of the pheromone that is responsible for storing collective knowledge. The presented two-dimensional pheromone is able to accommodate more information that is extracted from feasible solutions that can be used to improve the search of a solution space. The idea is positively evaluated on TSP and VRP problems, achieving better results as compared to the original algorithm. Since it is a universal concept, it can be applied to any single-objective problem that is solvable by ACO.
