Detail publikace

Reliability-Based Optimization: Small Sample Optimization Strategy.

Originální název

Reliability-Based Optimization: Small Sample Optimization Strategy.

Anglický název

Reliability-Based Optimization: Small Sample Optimization Strategy.

Jazyk

en

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.

Anglický 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.

BibTex


@article{BUT113722,
  author="Drahomír {Novák} and Ondřej {Slowik} and Maosen {Cao}",
  title="Reliability-Based Optimization: Small Sample Optimization Strategy.",
  annote="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.",
  chapter="113722",
  howpublished="print",
  number="11",
  volume="2",
  year="2014",
  month="october",
  pages="31--37",
  type="journal article - other"
}