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Structural and Multidisciplinary Optimization

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01.05.2014 | INDUSTRIAL APPLICATION

Approximate multi-objective optimization using conservative and feasible moving least squares method: application to automotive knuckle design

verfasst von: Chang Yong Song, Ha-Young Choi, Jongsoo Lee

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 5/2014

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Abstract

The original version of the moving least squares method (MLSM) does not always ensure solution feasibility for nonlinear and/or non-convex functions in the context of meta-model-based approximate optimization. The paper explores a new implementation of MLSM that ensures the conservative feasibility of Pareto optimal solutions in non-dominated sorting genetic algorithm (NSGA-II)-based approximate multi-objective optimization. We devised a ‘conservative and feasible MLSM’ (CF-MLSM) to realize the conservativeness and feasibility of multi-objective Pareto optimal solutions for both unconstrained and constrained problems. We verified the usefulness of our proposed approach by exploring strength-based sizing optimization of an automotive knuckle component under bump and brake loading constraints.

Vorheriger Artikel Uncertainty analysis on process responses of conventional spinning using finite element method

Nächster Artikel Automatic design of marine structures by using successive response surface method

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Titel: Approximate multi-objective optimization using conservative and feasible moving least squares method: application to automotive knuckle design
verfasst von: Chang Yong Song
Ha-Young Choi
Jongsoo Lee
Publikationsdatum: 01.05.2014
Verlag: Springer Berlin Heidelberg
Erschienen in: Structural and Multidisciplinary Optimization / Ausgabe 5/2014
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI: https://doi.org/10.1007/s00158-013-1009-3

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