Reliability-Based Optimization: Small Sample Optimization Strategy

Drahomír Novák^1*, Ondřej Slowik¹, Maosen Cao²

¹Institute of Structural Mechanics, Faculty of Civil Engineering Brno University of Technology, Brno, Czech Republic.
²Department of Engineering Mechanics, Hohai University, Nanjing, China.

DOI: 10.4236/jcc.2014.211004                

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 com- putational demands.

Keywords

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

Conflicts of Interest

The authors declare no conflicts of interest.

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