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Structural and Multidisciplinary Optimization

Erschienen in:

01.07.2012 | Research Paper

A random sampling approach to worst-case design of structures

verfasst von: Makoto Ohsaki, Masahiko Katsura

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 1/2012

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Abstract

A random sampling approach is presented for worst-case design of structures. Uncertainties are considered in structural and material parameters, which are assumed to exist in intervals with prescribed upper and lower bounds. Constraints are given for the worst responses that are found by solving anti-optimization problems. Optimal cross-sections are then selected from the list of available sections. The regions of uncertainty of parameters are discretized into integer values to formulate the hybrid problem of optimization and anti-optimization as an integer programming problem. The accuracy of solution is defined based on the order of the objective value; hence, a random sampling approach is successfully applied to obtain optimal and anti-optimal solutions within the prescribed accuracy. It is shown in the numerical examples that a good approximate optimal solution is found by random sampling with small number of analyses.

Vorheriger Artikel On the optimality of Hemp’s arch with vertical hangers

Nächster Artikel Convergence of topological patterns of optimal periodic structures under multiple scales

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Titel: A random sampling approach to worst-case design of structures
verfasst von: Makoto Ohsaki
Masahiko Katsura
Publikationsdatum: 01.07.2012
Verlag: Springer-Verlag
Erschienen in: Structural and Multidisciplinary Optimization / Ausgabe 1/2012
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI: https://doi.org/10.1007/s00158-011-0752-6

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