Přístupnostní navigace
E-přihláška
Vyhledávání Vyhledat Zavřít
Detail publikace
NOVÁK, D. SLOWIK, O. CAO, M.
Originální název
Reliability-Based Optimization: Small Sample Optimization Strategy.
Typ
článek v časopise - ostatní, Jost
Jazyk
angličtina
Originální abstrakt
The aim of the paper is to present a newly developed approach for reliability-based design optimization. It is based on double loop framework where the outer loop of algorithm covers the optimization part of process of reliability-based optimization and reliability constrains are calculated in inner loop. Innovation of suggested approach is in application of newly developed optimization strategy based on multilevel simulation using an advanced Latin Hypercube Sampling technique. This method is called Aimed multilevel sampling and it is designated for optimization of problems where only limited number of simulations is possible to perform due to enormous computational demands.
Klíčová slova
Optimization, Reliability Assessment, Aimed Multilevel Sampling, Monte Carlo, Latin Hypercube Sampling, Probability of Failure, Reliability-Based Design Optimization, Small Sample Analysis
Autoři
NOVÁK, D.; SLOWIK, O.; CAO, M.
Rok RIV
2014
Vydáno
15. 10. 2014
ISSN
2327-5219
Periodikum
Journal of Computer and Communications
Ročník
2
Číslo
11
Stát
Čínská lidová republika
Strany od
31
Strany do
37
Strany počet
7
BibTex
@article{BUT113722, author="Drahomír {Novák} and Ondřej {Slowik} and Maosen {Cao}", title="Reliability-Based Optimization: Small Sample Optimization Strategy.", journal="Journal of Computer and Communications", year="2014", volume="2", number="11", pages="31--37", issn="2327-5219" }