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A Note on Matrix Reordering for Linear System Solutions by Iterative Methods in Interior Point Methods

In: Operations Research Proceedings 2022

Author

Listed:
  • W. Rodrigues

    (UNIFACCAMP)

  • Marta Velazco

    (UNIFACCAMP)

  • A. R. L. Oliveira

    (IMECC-UNICAMP)

Abstract

The linear systems arising from interior point methods (IPM) for linear programming are solved using the preconditioned conjugate gradient method (PCG). Two preconditioners are adopted: the controlled Cholesky factorization (CCF) of the normal equations system and the splitting preconditioner. The CCF performance depends upon the previous reordering of the linear programming constraint matrix rows. A comparison among two different reordering methods is performed in order to verify the most suitable one for this approach. Variants of nested dissection (ND) and the minimum degree (MD) are among the considered heuristics. Computational experiments with large-scale linear programming problems from several collection sets are performed.

Suggested Citation

  • W. Rodrigues & Marta Velazco & A. R. L. Oliveira, 2023. "A Note on Matrix Reordering for Linear System Solutions by Iterative Methods in Interior Point Methods," Lecture Notes in Operations Research, in: Oliver Grothe & Stefan Nickel & Steffen Rebennack & Oliver Stein (ed.), Operations Research Proceedings 2022, chapter 0, pages 79-85, Springer.
    • Handle: RePEc:spr:lnopch:978-3-031-24907-5_10
    DOI: 10.1007/978-3-031-24907-5_10
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