https://scholars.lib.ntu.edu.tw/handle/123456789/403706
Title: | Active-set sequential quadratic programming with variable probabilistic constraint evaluations for optimization problems under non-Gaussian uncertainties | Authors: | Chan, K.-Y. Huang, Y.-C. |
Issue Date: | 2010 | Source: | Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science | Abstract: | Design optimization under random uncertainties are formulated as problems with probabilistic constraints. Calculating these constraints presents a major challenge in the optimization. While most research concentrates on uncertainties that are Gaussian, a great number of uncertainties in the environment are non-Gaussian. In this work, various reliability analyses for non-Gaussian uncertainties within a sequential quadratic programming framework are integrated. An analytical reliability contour (RC) is first constructed in the design space to indicate the minimal distance from the feasible boundary of a design at a desired reliability level. A safe zone contour is then created so as to provide a quick estimate of the RC. At each design iteration reliability analyses of different accuracies are selected based on the level needed, depending on the activity of a constraint. For problems with a large number of constraints and relatively few design variables, such as structural problems, the active set strategies significantly improve efficiency, as demonstrated in the examples. © 2010 Authors. |
URI: | http://www.scopus.com/inward/record.url?eid=2-s2.0-77953953268&partnerID=MN8TOARS https://scholars.lib.ntu.edu.tw/handle/123456789/403706 |
ISSN: | 09544062 | DOI: | 10.1243/09544062JMES1742 |
Appears in Collections: | 機械工程學系 |
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