Approximation methods in multidisciplinary analysis and optimization: a panel discussion

By Timothy W. Simpson, A. Booker, D. Ghosh, Anthony A. Giunta, Patrick N. Koch, Ren-Jye Yang. 2004

463 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d242ef864e94cc8b0f836f2c87e5907cf35a9411

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In Computational Theory and Mathematics

In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Multi-objective topology optimization of multi-component continuum structures via a Kriging-interpolated level set approach (2014, methodology): “2013b), which defines the design variables as the level-set function values at knot points that are interpolated in the rest of the design domain via a Kriging model (Simpson et al. 2004).”
Reduced-Order Nonlinear Unsteady Aerodynamic Modeling Using a Surrogate-Based Recurrence Framework (2010, background): “Under these conditions, the DOE need only be space-filling [26,29] so that all regions of the input parameter space are sampled.”
Design and Analysis of Computer Experiments in Multidisciplinary Design Optimization: A Review of How Far We Have Come - Or Not (2008, background): “5 As discussed in the panel, metamodels are finding a variety of new uses, including optimization under uncertainty, which is receiving considerable attention as of late, 78 and robust design and reliability-based design since they provided inexpensive surrogates for Monte Carlo simulation and…”
Kriging metamodeling in simulation: A review (2009, unknown): “Key words: Kriging, Metamodel, Response Surface, Interpolation, Design JEL: C0, C1, C9”
Use of Kriging Models to Approximate Deterministic Computer Models (2005, methodology): “As a more computationally efficient alternative, cross-validation (CV) [2,47,48] or Akaike’s information criteria (AIC) can be used [49,50].”
A benchmark of kriging-based infill criteria for noisy optimization (2013, methodology): “The use of kriging for modeling and optimizing deterministic computer simulations has a long and successful tradition [30, 20, 37, 21].”
Review of surrogate modeling in water resources (2012, background): “Note that problems with discrete or mixed variables require special considerations and have been solved largely on an ad hoc basis [Simpson et al., 2004].”
Metamodeling in Multidisciplinary Design Optimization: How Far Have We Really Come? (2014, background): “Specifically, Table 6 Commercial software metamodeling and optimization capabilities Software product Metamodeling capabilities Optimization capabilities BOSS/Quattro (LMS International) http://www.lmsintl.com/samtechboss-quattro Least-squares regression for polynomials and posynomials, radial-basis”
Pitfalls of using a single criterion for selecting experimental designs (2008, background): “There have been some studies on the influence of different experimental designs (EDs) on predictions [1–4].”
Review of Metamodeling Techniques in Support of Engineering Design Optimization (2007, background): “The summary of the panel discussion was archived in [6].”
Survey of modeling and optimization strategies to solve high-dimensional design problems with computationally-expensive black-box functions (2010, background): “Intensive research has been done on the multidisciplinary design optimization (Kodiyalam and Sobieszczanski-Sobieski 2000; Simpson et al. 2004) and applied in industry (Sobieszczanski-Sobieski and Haftka 1997).”
Update strategies for kriging models used in variable fidelity optimization (2006, methodology): “Since this time, it has been widely used to approximate computer models (Booker et al. 1999; Gano et al. 2005b; Giunta and Watson 1998; Chung and Alonso 2002b; 288 S. E. Gano et al. Simpson et al. 2001c, 2004 ).”