Article citationsMore>>

Dubourg, V., Bourinet, J.M. and Sudret, B. (2010) A Hierarchical Surrogate-based Strategy for Reliability-Based Design Optimization. In: Straub, D., Esteva, L. and Faber, M., Eds., Proceedings 15th IFIP WG7.5 Conference on Reliability and Optimization of Structural Systems, Taylor & Francis, Munich, Germany, 53-60.

has been cited by the following article:

• TITLE: Reliability-Based Optimization: Small Sample Optimization Strategy

  AUTHORS: Drahomír Novák, Ondřej Slowik, Maosen Cao

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

  JOURNAL NAME: Journal of Computer and Communications, Vol.2 No.11, September 12, 2014

  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.