Abstract
Large-scale design optimization problems frequently require the exploitation of structure in order to obtain efficient and reliable solutions. Successful algorithms for general nonlinear programming problems with theoretical underpinnings do not usually accommodate any additional structure within the problem. In this article modifications are made to a trust region algorithm to take advantage of hierarchical structure without compromising the theoretical properties of the original algorithm.
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Communicated by J. Sobieski
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Nelson, S.A., Papalambros, P.Y. A modified trust region algorithm for hierarchical NLP. Structural Optimization 16, 19–28 (1998). https://doi.org/10.1007/BF01213996
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DOI: https://doi.org/10.1007/BF01213996