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A combined reordering procedure for preconditioned GMRES applied to solving equations using Lagrange multiplier method

Zixiang Hu (State Key Laboratory of Material Processing and Die & Mold Technology, Huazhong University of Science and Technology, Wuhan, P.R. China)
Zhenmin Wang (School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, P.R. China)
Shi Zhang (State Key Laboratory of Material Processing and Die & Mold Technology, Huazhong University of Science and Technology, Wuhan, P.R. China)
Yun Zhang (State Key Laboratory of Material Processing and Die & Mold Technology, Huazhong University of Science and Technology, Wuhan, P.R. China)
Huamin Zhou (State Key Laboratory of Material Processing and Die & Mold Technology, Huazhong University of Science and Technology, Wuhan, P.R. China and Research Institute of Huazhong University of Science and Technology in Shenzhen, Shenzhen, P.R. China)

Engineering Computations

ISSN: 0264-4401

Article publication date: 30 September 2014

191

Abstract

Purpose

The purpose of this paper is to propose a combined reordering scheme with a wide range of application, called Reversed Cuthill-McKee-approximate minimum degree (RCM-AMD), to improve a preconditioned general minimal residual method for solving equations using Lagrange multiplier method, and facilitates the choice of the reordering for the iterative method.

Design/methodology/approach

To reordering the coefficient matrix before a preconditioned iterative method will greatly impact its convergence behavior, but the effect is very problem-dependent, even performs very differently when different preconditionings applied for an identical problem or the scale of the problem varies. The proposed reordering scheme is designed based on the features of two popular ordering schemes, RCM and AMD, and benefits from each of them.

Findings

Via numerical experiments for the cases of various scales and difficulties, the effects of RCM-AMD on the preconditioner and the convergence are investigated and the comparisons of RCM, AMD and RCM-AMD are presented. The results show that the proposed reordering scheme RCM-AMD is appropriate for large-scale and difficult problems and can be used more generally and conveniently. The reason of the reordering effects is further analyzed as well.

Originality/value

The proposed RCM-AMD reordering scheme preferable for solving equations using Lagrange multiplier method, especially considering that the large-scale and difficult problems are very common in practical application. This combined reordering scheme is more wide-ranging and facilitates the choice of the reordering for the iterative method, and the proposed iterative method has good performance for practical cases in in-house and commercial codes on PC.

Keywords

Acknowledgements

The authors would like to acknowledge the financial support from the National Natural Science Foundation Council of China (Grant No. 51125021, 51105152), the Major State Basic Research Project of China (Grant No. 2012CB025900) and the Shenzhen Basic Research Fund (Grant No. JC201005280644A, JC201105160599A).

Citation

Hu, Z., Wang, Z., Zhang, S., Zhang, Y. and Zhou, H. (2014), "A combined reordering procedure for preconditioned GMRES applied to solving equations using Lagrange multiplier method", Engineering Computations, Vol. 31 No. 7, pp. 1283-1304. https://doi.org/10.1108/EC-07-2013-0184

Publisher

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Emerald Group Publishing Limited

Copyright © 2014, Emerald Group Publishing Limited

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