Differential EvolutionAlgorithm in Models of Technical Optimization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24510%2F21%3A00009457" target="_blank" >RIV/46747885:24510/21:00009457 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.7148/2021-0179" target="_blank" >https://doi.org/10.7148/2021-0179</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.7148/2021" target="_blank" >10.7148/2021</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Differential EvolutionAlgorithm in Models of Technical Optimization

Popis výsledku v původním jazyce

At present, evolutionary optimization algorithms are increasingly used in the development of new technological processes. Evolutionary algorithms often allow the optimization procedure to be performed even in cases where classical optimization algorithms fail (e.g. gradient methods) and where an acceptable solution is sufficient to solve the optimization task. The article focuses on possibilities of using a differential evolution algorithm in the optimization process. This algorithm is often referred to in the literature as a global optimization procedure. However, we show by means of a practical example that the convergence of the classic differential algorithm to the global extreme is not generally assured and is largely dependent on the specific cost function. To remove this weakness, we designed a modified version of the differential evolution algorithm. The improved version, named the modified differential evolution algorithm, is described in the article. It is possible to prove asymptotic convergence to the global minimum of the cost function for the modified version of the algorithm.

Název v anglickém jazyce

Differential EvolutionAlgorithm in Models of Technical Optimization

Popis výsledku anglicky

At present, evolutionary optimization algorithms are increasingly used in the development of new technological processes. Evolutionary algorithms often allow the optimization procedure to be performed even in cases where classical optimization algorithms fail (e.g. gradient methods) and where an acceptable solution is sufficient to solve the optimization task. The article focuses on possibilities of using a differential evolution algorithm in the optimization process. This algorithm is often referred to in the literature as a global optimization procedure. However, we show by means of a practical example that the convergence of the classic differential algorithm to the global extreme is not generally assured and is largely dependent on the specific cost function. To remove this weakness, we designed a modified version of the differential evolution algorithm. The improved version, named the modified differential evolution algorithm, is described in the article. It is possible to prove asymptotic convergence to the global minimum of the cost function for the modified version of the algorithm.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10102 - Applied mathematics

Projekt

<a href="/cs/project/EF16_025%2F0007293" target="_blank" >EF16_025/0007293: Modulární platforma pro autonomní podvozky specializovaných elektrovozidel pro dopravu nákladu a zařízení</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Communications of the ECMS , Volume 35, Issue 1, June 2021

ISBN

978-3-937436-72-2

ISSN

2522-2422

e-ISSN

—

Počet stran výsledku

6

Strana od-do

179-184

Název nakladatele

Communications of the ECMS , Volume 35, Issue 1, June 2021

Místo vydání

United Kingdom

Místo konání akce

on-line

Datum konání akce

1. 1. 2021

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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