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Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/17231

Title: Progressive Validity Metamodel Trust Region Optimization
Authors: Thomson, Quinn Parker
Advisor: Martins, Joaquim R. R. A.
Department: Aerospace Science and Engineering
Keywords: Multidisciplinary Optimization
Metamodels
Response Surfaces
Surrogate Models
Trust Region Optimization
Progressive Validity
Leave-k-out Cross-Validation
Concurrent Subspace Optimization
Issue Date: 26-Feb-2009
Abstract: The goal of this work was to develop metamodels of the MDO framework piMDO and provide new research in metamodeling strategies. The theory of existing metamodels is presented and implementation details are given. A new trust region scheme --- metamodel trust region optimization (MTRO) --- was developed. This method uses a progressive level of minimum validity in order to reduce the number of sample points required for the optimization process. Higher levels of validity require denser point distributions, but the reducing size of the region during the optimization process mitigates an increase the number of points required. New metamodeling strategies include: inherited optimal latin hypercube sampling, hybrid latin hypercube sampling, and kriging with BFGS. MTRO performs better than traditional trust region methods for single discipline problems and is competitive against other MDO architectures when used with a CSSO algorithm. Advanced metamodeling methods proved to be inefficient in trust region methods.
URI: http://hdl.handle.net/1807/17231
Appears in Collections:Master
Institute for Aerospace Studies - Master theses

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