Szczegóły publikacji
Opis bibliograficzny
Efficient memetic continuous optimization in agent-based computing / Wojciech KORCZYŃSKI, Aleksander BYRSKI, Marek KISIEL-DOROHINICKI // Procedia Computer Science [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 1877-0509. — 2016 — vol. 80, s. 845–854. — Wymagania systemowe: Adobe Redaer. — Bibliogr. s. 853–854, Abstr. — ICCS 2016 : the International Conference on Computational Science : 6–8 June, San Diego, USA
Autorzy (3)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 98331 |
|---|---|
| Data dodania do BaDAP | 2016-06-30 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.procs.2016.05.374 |
| Rok publikacji | 2016 |
| Typ publikacji | referat w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Procedia Computer Science |
Abstract
This paper deals with a concept of memetic search in agent-based evolutionary computation. In the presented approach, local search is applied during mutation of an agent. Using memetic algorithms causes increased demand on the computing power as the number of fitness function calls increases, therefore careful planning of the fitness computing (through the proposed local search mechanism based on caching parts of the fitness function) leads to significant lowering of this demand. Moreover, applying local search with care, can lead to gradual improvement of the whole population. In the paper the results obtained for selected high-dimensional (5000 dimensions) benchmark functions are presented. Results obtained by the evolutionary and memetic multi-agent systems are compared with classic evolutionary algorithm.