확률조건의 근사화를 통한 효율적인 강건 최적설계 기법의 개발Development of an Efficient Optimization Technique for Robust Design by Approximating Probability Constratints

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Alternative formulation is presented for robust optimization problems and an efficient computational scheme for reliability estimation is proposed. Both design variables and design parameters considered as random variables about their nominal values. To ensure the robustness of objective performance a new cost function bounding the performance and a new constraint limiting the performance variation are introduced. The constraint variations are regulated by considering the probability of feasibility. Each probability constraint is transformed into a sub-optimization problem and then is resolved with the modified advanced first order second moment(AFOSM) method for computational efficiency. The proposed robust optimization method has advantages that the mean value and the variation of the performance function are controlled simultaneously and the second order sensitivity information is not required even in case of gradient based optimization. The suggested method is examined by solving three examples and the results are compared with those for deterministic case and those available in literature.
Publisher
대한기계학회
Issue Date
2000-12
Language
Korean
Citation

대한기계학회논문집 A, v.24, no.12, pp.3053 - 3060

ISSN
1226-4873
URI
http://hdl.handle.net/10203/75770
Appears in Collection
ME-Journal Papers(저널논문)
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