Surrogate-Assisted Differential Evolution-Based Method for the ICSI’2022 Competition

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F22%3APU144872" target="_blank" >RIV/00216305:26210/22:PU144872 - isvavai.cz</a>
Výsledek na webu
<a href="https://link.springer.com/chapter/10.1007/978-3-031-09726-3_40" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-09726-3_40</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-09726-3_40" target="_blank" >10.1007/978-3-031-09726-3_40</a>

Jazyk výsledku
angličtina
Název v původním jazyce
Surrogate-Assisted Differential Evolution-Based Method for the ICSI’2022 Competition
Popis výsledku v původním jazyce
In this paper, a method called Lipschitz-surrogate Assisted Differential Evolution (LSADE) is described. The method uses two different surrogates: a standard radial basis function one and a specialized one based on a Lipschitz condition. It also uses two optimization methods: differential evolution and sequential quadratic programming. The LSADE method is investigated on the benchmark set of the ICSI’2022 competition and is compared with two other high-performing methods for bound constrained optimization, outperforming them both on the studied benchmark set.
Název v anglickém jazyce
Surrogate-Assisted Differential Evolution-Based Method for the ICSI’2022 Competition
Popis výsledku anglicky
In this paper, a method called Lipschitz-surrogate Assisted Differential Evolution (LSADE) is described. The method uses two different surrogates: a standard radial basis function one and a specialized one based on a Lipschitz condition. It also uses two optimization methods: differential evolution and sequential quadratic programming. The LSADE method is investigated on the benchmark set of the ICSI’2022 competition and is compared with two other high-performing methods for bound constrained optimization, outperforming them both on the studied benchmark set.

Druh
C - Kapitola v odborné knize
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku
Advances in Swarm Intelligence. ICSI 2022, Part II. Lecture Notes in Computer Science, vol 13345.
ISBN
978-3-031-09726-3
Počet stran výsledku
10
Strana od-do
440-449
Počet stran knihy
454
Název nakladatele
Springer, Cham
Místo vydání
Neuveden
Kód UT WoS kapitoly
—

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