Publication detail

Reliability-Based Optimization: Small Sample Optimization Strategy.

NOVÁK, D. SLOWIK, O. CAO, M.

Original Title

Reliability-Based Optimization: Small Sample Optimization Strategy.

Type

journal article - other

Language

English

Original Abstract

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.

Keywords

Optimization, Reliability Assessment, Aimed Multilevel Sampling, Monte Carlo, Latin Hypercube Sampling, Probability of Failure, Reliability-Based Design Optimization, Small Sample Analysis

Authors

NOVÁK, D.; SLOWIK, O.; CAO, M.

RIV year

2014

Released

15. 10. 2014

ISBN

2327-5219

Periodical

Journal of Computer and Communications

Year of study

2

Number

11

State

People's Republic of China

Pages from

31

Pages to

37

Pages count

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"
}