Self-organizing migrating algorithm: review, improvements and comparison
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10249947" target="_blank" >RIV/61989100:27240/22:10249947 - isvavai.cz</a>
Výsledek na webu
<a href="https://link.springer.com/content/pdf/10.1007/s10462-022-10167-8.pdf" target="_blank" >https://link.springer.com/content/pdf/10.1007/s10462-022-10167-8.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10462-022-10167-8" target="_blank" >10.1007/s10462-022-10167-8</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Self-organizing migrating algorithm: review, improvements and comparison
Popis výsledku v původním jazyce
The self-organizing migrating algorithm (SOMA) is a population-based meta-heuristic that belongs to swarm intelligence. In the last 20 years, we can observe two main streams in the publications. First, novel approaches contributing to the improvement of its performance. Second, solving the various optimization problems. Despite the different approaches and applications, there exists no work summarizing them. Therefore, this work reviews the research papers dealing with the principles and application of the SOMA. The second goal of this work is to provide additional information about the performance of the SOMA. This work presents the comparison of the selected algorithms. The experimental results indicate that the best-performing SOMAs provide competitive results comparing the recently published algorithms. (C) 2022, The Author(s).
Název v anglickém jazyce
Self-organizing migrating algorithm: review, improvements and comparison
Popis výsledku anglicky
The self-organizing migrating algorithm (SOMA) is a population-based meta-heuristic that belongs to swarm intelligence. In the last 20 years, we can observe two main streams in the publications. First, novel approaches contributing to the improvement of its performance. Second, solving the various optimization problems. Despite the different approaches and applications, there exists no work summarizing them. Therefore, this work reviews the research papers dealing with the principles and application of the SOMA. The second goal of this work is to provide additional information about the performance of the SOMA. This work presents the comparison of the selected algorithms. The experimental results indicate that the best-performing SOMAs provide competitive results comparing the recently published algorithms. (C) 2022, The Author(s).
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10200 - Computer and information sciences
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Artificial Intelligence Review
ISSN
0269-2821
e-ISSN
1573-7462
Svazek periodika
Neuveden
Číslo periodika v rámci svazku
Duben 2022
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
72
Strana od-do
nestrankovano
Kód UT WoS článku
000778060000001
EID výsledku v databázi Scopus
2-s2.0-85127552404