Multi-Objective Optimization with Asymptotic Sampling for RBDO

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F13%3A00206798" target="_blank" >RIV/68407700:21110/13:00206798 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Multi-Objective Optimization with Asymptotic Sampling for RBDO

Popis výsledku v původním jazyce

This paper is focused on multi-objective reliability-based design optimization. A weight of a structure and a probability of failure represented by a reliability index form two competing objectives. Since the probability of failure of realistic structures is low, e.g. 10-4 - 10-5 for ultimate limit states in the case of civil engineering structures, the required number of samples for crude Monte Carlo is overwhelming. Even the application of quasi Monte Carlo methods such as Latin Hypercube Sampling does not bring substantial reduction of the required computational time and therefore, an approximate method called asymptotic sampling for prediction of the probability of failure and/or the reliability index is used. Here, an application of multi-objective optimization to reliability-based design optimization is twofold: (i) single-objective optimization is usually not able to find all optima in a multimodal problem thus the multi-objective algorithm based on a non-dominated sorting genet

Název v anglickém jazyce

Multi-Objective Optimization with Asymptotic Sampling for RBDO

Popis výsledku anglicky

This paper is focused on multi-objective reliability-based design optimization. A weight of a structure and a probability of failure represented by a reliability index form two competing objectives. Since the probability of failure of realistic structures is low, e.g. 10-4 - 10-5 for ultimate limit states in the case of civil engineering structures, the required number of samples for crude Monte Carlo is overwhelming. Even the application of quasi Monte Carlo methods such as Latin Hypercube Sampling does not bring substantial reduction of the required computational time and therefore, an approximate method called asymptotic sampling for prediction of the probability of failure and/or the reliability index is used. Here, an application of multi-objective optimization to reliability-based design optimization is twofold: (i) single-objective optimization is usually not able to find all optima in a multimodal problem thus the multi-objective algorithm based on a non-dominated sorting genet

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

<a href="/cs/project/GAP105%2F12%2F1146" target="_blank" >GAP105/12/1146: Metody paralelizace inženýrských úloh využívající cenově dostupné technologie</a><br>

Návaznosti

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

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the Third International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering

ISBN

978-1-905088-58-4

ISSN

1759-3433

e-ISSN

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Počet stran výsledku

12

Strana od-do

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Název nakladatele

Civil-Comp Press Ltd

Místo vydání

Stirling

Místo konání akce

Cagliari

Datum konání akce

3. 9. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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