Sequential Convex Programming Methods for Solving Large Topology Optimization Problems: Implementation and Computational Results

Sequential Convex Programming Methods for Solving Large Topology Optimization Problems: Implementation and Computational Results

Year:    2005

Author:    Qin Ni, Ch. Zillober, K. Schittkowski

Journal of Computational Mathematics, Vol. 23 (2005), Iss. 5 : pp. 491–502

Abstract

In this paper, we describe a method to solve large-scale structural optimization problems by sequential convex programming (SCP). A predictor-corrector interior point method is applied to solve the strictly convex subproblems. The SCP algorithm and the topology optimization approach are introduced. Especially, different strategies to solve certain linear systems of equations are analyzed. Numerical results are presented to show the efficiency of the proposed method for solving topology optimization problems and to compare different variants. 

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/2005-JCM-8834

Journal of Computational Mathematics, Vol. 23 (2005), Iss. 5 : pp. 491–502

Published online:    2005-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    12

Keywords:    Large scale optimization Topology optimization Sequential convex programming method Predictor-corrector interior point method Method of moving asymptotes.

Author Details

Qin Ni

Ch. Zillober

K. Schittkowski