A new interval uncertain optimization method for structures using Chebyshev surrogate models

Publication Type:
Journal Article
Citation:
Computers and Structures, 2015, 146 pp. 185 - 196
Issue Date:
2015-01-01
Full metadata record
Files in This Item:
Filename Description Size
ThumbnailCS.pdfPublished Version2.48 MB
Adobe PDF
© 2014 Elsevier Ltd. All rights reserved. This paper proposes a new non-probabilistic interval uncertain optimization methodology for structures. The uncertain design problem is often formulated as a double-loop optimization. Interval arithmetic is introduced to directly evaluate the bounds of interval functions and eliminate the inner loop optimization. A high-order Taylor inclusion function is proposed to compress the overestimation of interval arithmetic. A Chebyshev surrogate model is proposed to approximate the high-order coefficients of the inclusion function. A metaheuristic optimization algorithm is combined with the mathematical programming to search the global optimum. Two numerical examples are used to demonstrate the effectiveness of this method.
Please use this identifier to cite or link to this item: