Bayes approach to solving T.E.A.M. benchmark problems 22 and 25 and its comparison with other optimization techniques

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F18%3A43932182" target="_blank" >RIV/49777513:23220/18:43932182 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.sciencedirect.com/science/article/pii/S0096300317305040" target="_blank" >http://www.sciencedirect.com/science/article/pii/S0096300317305040</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.amc.2017.07.043" target="_blank" >10.1016/j.amc.2017.07.043</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Bayes approach to solving T.E.A.M. benchmark problems 22 and 25 and its comparison with other optimization techniques

Popis výsledku v původním jazyce

The Bayes approach is used for solution of benchmark problems 22 and 25. The main purpose of the paper is to evaluate its applicability for solving complex technical problems (up to now, this technique was only very rarely used in the domain of such tasks). The parameters of this approach are compared with characteristics of several other heuristic and deterministic optimization techniques implemented in commercial code COMSOL Multiphysics and own open-source application Agros Suite. The results confirm that the Bayes approach is superior in a number of aspects and for the solution of real-life tasks it represents a powerful and prospective alternative to existing optimization methods.

Název v anglickém jazyce

Bayes approach to solving T.E.A.M. benchmark problems 22 and 25 and its comparison with other optimization techniques

Popis výsledku anglicky

The Bayes approach is used for solution of benchmark problems 22 and 25. The main purpose of the paper is to evaluate its applicability for solving complex technical problems (up to now, this technique was only very rarely used in the domain of such tasks). The parameters of this approach are compared with characteristics of several other heuristic and deterministic optimization techniques implemented in commercial code COMSOL Multiphysics and own open-source application Agros Suite. The results confirm that the Bayes approach is superior in a number of aspects and for the solution of real-life tasks it represents a powerful and prospective alternative to existing optimization methods.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

<a href="/cs/project/LO1607" target="_blank" >LO1607: RICE – Nové technologie a koncepce pro inteligentní průmyslové systémy</a><br>

Návaznosti

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

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Applied Mathematics and Computation

ISSN

0096-3003

e-ISSN

—

Svazek periodika

319

Číslo periodika v rámci svazku

15 February

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

12

Strana od-do

681-692

Kód UT WoS článku

000415906200053

EID výsledku v databázi Scopus

2-s2.0-85026756954