MIXED VARIABLE STRUCTURAL OPTIMIZATION USING CONVEX LINEARIZATION TECHNIQUES

Abstract

In this paper, the use of convex approximation techniques is investigated for optimizing the configuration of planar trusses. It has been previously shown that simultaneous treatment of sizing and configuration variables is feasible. This work demonstrates that not only do the two types of variables not require separation but that they can be handled efficiently together. Problems with both types of variables can be solved within a small number of analyses (typically ten) This work also indicates that approximation techniques can be used to great advantage on problems with both configuration and sizing variables. The addition of the second type of design variable causes little increase in the computational difficulty of the problem. The use of approximation techniques improves the convergence properties and greatly reduces the number of analyses required Various convex linearization schemes are investigated on problems of shape optimization of truss structures. In particular, the Convex Linearization Method is compared with a recent generalization called the Method of Moving Asymptotes. Numerical results for several examples with stress and displacement constraints are given to illustrate the convergence properties of the methods.