Reliability-Based Optimization: Small Sample Optimization Strategy

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DOI: 10.4236/jcc.2014.211004    2,694 Downloads   3,593 Views  Citations

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.

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Novák, D. , Slowik, O. and Cao, M. (2014) Reliability-Based Optimization: Small Sample Optimization Strategy. Journal of Computer and Communications, 2, 31-37. doi: 10.4236/jcc.2014.211004.

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