Přístupnostní navigace
E-application
Search Search Close
Publication detail
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" }