Detail publikace

Reliability-Based Optimization: Small Sample Optimization Strategy.

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"
}