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

Wu, J; Luo, Z; Zhang, N; Zhang, Y

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

Wu, J

Luo, Z

Zhang, N

Zhang, Y

Permalink

Publication Type:: Journal Article
Citation:: Computers and Structures, 2015, 146 pp. 185 - 196
Issue Date:: 2015-01-01

Closed Access

	Filename	Description	Size
	CS.pdf	Published Version	2.48 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Wu, J https://orcid.org/0000-0002-4925-4242	en_US
dc.contributor.author	Luo, Z https://orcid.org/0000-0002-6953-3986	en_US
dc.contributor.author	Zhang, N https://orcid.org/0000-0001-6408-0044	en_US
dc.contributor.author	Zhang, Y	en_US
dc.date.issued	2015-01-01	en_US
dc.identifier.citation	Computers and Structures, 2015, 146 pp. 185 - 196	en_US
dc.identifier.issn	0045-7949	en_US
dc.identifier.uri	http://hdl.handle.net/10453/33964
dc.description.abstract	© 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.	en_US
dc.relation.ispartof	Computers and Structures	en_US
dc.relation.isbasedon	10.1016/j.compstruc.2014.09.006	en_US
dc.subject.classification	Applied Mathematics	en_US
dc.title	A new interval uncertain optimization method for structures using Chebyshev surrogate models	en_US
dc.type	Journal Article
utslib.citation.volume	146	en_US
utslib.for	091307 Numerical Modelling and Mechanical Characterisation	en_US
utslib.for	09 Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	146	en_US

Abstract:

© 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:

http://hdl.handle.net/10453/33964