Szczegóły publikacji
Opis bibliograficzny
Applying autonomous hybrid agent-based computing to difficult optimization problems / Mateusz GODZIK, Jacek DAJDA, Marek KISIEL-DOROHINICKI, Aleksander BYRSKI, Leszek RUTKOWSKI, Patryk Orzechowski, Joost Wagenaar, Jason H. Moore // Journal of Computational Science ; ISSN 1877-7503. — 2022 — vol. 64 art. no. 101858, s. 1–13. — Bibliogr. s. 12, Abstr. — Publikacja dostępna online od: 2022-09-17. — P. Orzechowski - afiliacja: University of Pennsylvania, USA
Autorzy (8)
- AGHGodzik Mateusz
- AGHDajda Jacek
- AGHKisiel-Dorohinicki Marek
- AGHByrski Aleksander
- AGHRutkowski Leszek
- Orzechowski Patryk
- Wagenaar Joost
- Moore Jason H.
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 142818 |
|---|---|
| Data dodania do BaDAP | 2022-11-28 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.jocs.2022.101858 |
| Rok publikacji | 2022 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Journal of Computational Science |
Abstract
Evolutionary multi-agent systems (EMASs) are very good at dealing with difficult, multi-dimensional problems, their efficacy was proven theoretically based on analysis of the relevant Markov-Chain based model. Now the research continues on introducing autonomous hybridization into EMAS. This paper focuses on a proposed hybrid version of the EMAS, and covers selection and introduction of a number of hybrid operators and defining rules for starting the hybrid steps of the main algorithm. Those hybrid steps leverage existing, well-known and proven to be efficient metaheuristics, and integrate their results into the main algorithm. The discussed modifications are evaluated based on a number of difficult continuous-optimization benchmarks.
