Volume 23, Issue 5
Sequential Convex Programming Methods for Solving Large Topology Optimization Problems: Implementation and Computational Results

Qin Ni, Ch. Zillober K. Schittkowski

J. Comp. Math., 23 (2005), pp. 491-502.

Published online: 2005-10

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  • 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. 

  • Keywords

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

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COPYRIGHT: © Global Science Press

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@Article{JCM-23-491, author = {Qin Ni , and Ch. Zillober , and K. Schittkowski , }, title = {Sequential Convex Programming Methods for Solving Large Topology Optimization Problems: Implementation and Computational Results }, journal = {Journal of Computational Mathematics}, year = {2005}, volume = {23}, number = {5}, pages = {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. 

}, issn = {1991-7139}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jcm/8834.html} }
TY - JOUR T1 - Sequential Convex Programming Methods for Solving Large Topology Optimization Problems: Implementation and Computational Results AU - Qin Ni , AU - Ch. Zillober , AU - K. Schittkowski , JO - Journal of Computational Mathematics VL - 5 SP - 491 EP - 502 PY - 2005 DA - 2005/10 SN - 23 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jcm/8834.html KW - Large scale optimization, Topology optimization, Sequential convex programming method, Predictor-corrector interior point method, Method of moving asymptotes. AB -

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. 

Qin Ni, Ch. Zillober & K. Schittkowski. (1970). Sequential Convex Programming Methods for Solving Large Topology Optimization Problems: Implementation and Computational Results . Journal of Computational Mathematics. 23 (5). 491-502. doi:
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