Reliability-based optimal design using sample average approximations

By Johannes O. Royset, Elijah Polak. 2004

103 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/269f13fd96d70a82afc648cb0bebab519269966e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

In Statistics and Probability

Citations in the corpus

Reliability-based optimization of stochastic systems using line search (2009, methodology): “An approach for estimating probability sensitivity with respect to deterministic variables was introduced in [35]; this approach requires solving the equation jiðfxg; fzgÞ 1⁄4 0 for one component of fzg, either by means of analytical or numerical procedures; however, this can be an involved task, sp”
Reliability-based design optimization using kriging surrogates and subset simulation (2011, methodology): “For such cases however, Royset and Polak (2004a,b) proposed the so-called sample average approximation method which consists in gradually reﬁning the simulation-based reliability analysis as the optimization algorithm converges towards an optimal design.”
Design sensitivity and reliability-based structural optimization by univariate decomposition (2008, methodology): “…reliability analysis: (1) the first-order reliability method (FORM; Enevoldsen and Sorensen 1994; Kuschel and Rackwitz 1997; Kirjner-Neto et al. 1998; Chiralaksanakul and Mahadevan 2005; Tu et al. 1999; Agarwal and Renaud 2006) and (2) simulation methods (Royset and Polak 2004; Qu and Haftka 2004).”
Monte Carlo sampling-based methods for stochastic optimization (2014, background): “For stochastic nonlinear programs, Polak and Royset [196] propose a control problem that aims to minimize the computational effort required to reduce an initial optimality gap by a prespecified fraction in the context of so-called diagonalization schemes.”
A survey on approaches for reliability-based optimization (2010, background): “The introduction of efficient strategies and approximation concepts also play a fundamental role in yielding challenging RBO problems tractable (see, e.g. Royset and Polak (2004b); Du and Chen (2004); Chen et al (1997)).”