A modification of convex approximation methods for structural optimization

[en] The most popular convex approximation methods used today in structural optimization are discussed in this paper: the convex linearization method (CONLIN), the method of the moving asymptotes (MMA) and the sequential quadratic programming method (SQP). Modifications are made to enhance the reliability of the CONLIN method. In addition, a generalized MMA (GMMA) is established. However, in view of practical difficulties of evaluating second-order derivatives, a fitting scheme is proposed in this work to adjust the convexity of the approximation based on the available function value at the preceding design iteration. Numerical results show that this simple scheme is efficient in our applications.

Disciplines :

Computer science
Engineering, computing & technology: Multidisciplinary, general & others
Mechanical engineering

Author, co-author :

Zhang, Wei-Hong; Aerospace Laboratory, LTAS, University of Liège, 4000-, Liège, Belgium

Fleury, Claude ; Université de Liège - ULiège > Département d'aérospatiale et mécanique > LTAS - Optimisation multidisciplinaire

Language :

English

Title :

A modification of convex approximation methods for structural optimization

Publication date :

1997

Journal title :

Computers and Structures

ISSN :

0045-7949

Publisher :

Pergamon Press - An Imprint of Elsevier Science, Oxford, United Kingdom

Volume :

Issue :

1-4

Pages :

89-95

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 08 June 2011

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Bibliography

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