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Projected fixed point iterative method for large and sparse horizontal linear complementarity problem

Author

Listed:
  • Bharat Kumar

    (PDPM-Indian Institute of Information Technology Design and Manufacturing)

  • Deepmala

    (PDPM-Indian Institute of Information Technology Design and Manufacturing)

  • A. K. Das

    (Indian Statistical Institute)

Abstract

For solving the horizontal linear complementarity problem, we propose two projected fixed-point matrix splitting methods. The first method is based on matrix splitting, while the second method is based on the Gauss–Seidel method. We provide some convergence conditions when the system matrices are $$H_+$$ H + -matrices. The efficiency of the proposed method is illustrated using two numerical examples for various parameters.

Suggested Citation

  • Bharat Kumar & Deepmala & A. K. Das, 2024. "Projected fixed point iterative method for large and sparse horizontal linear complementarity problem," Indian Journal of Pure and Applied Mathematics, Springer, vol. 55(2), pages 716-725, June.
    • Handle: RePEc:spr:indpam:v:55:y:2024:i:2:d:10.1007_s13226-023-00403-4
    DOI: 10.1007/s13226-023-00403-4
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    References listed on IDEAS

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    1. Francesco Mezzadri & Emanuele Galligani, 2019. "Splitting Methods for a Class of Horizontal Linear Complementarity Problems," Journal of Optimization Theory and Applications, Springer, vol. 180(2), pages 500-517, February.
    2. A. K. Das, 2016. "Properties of some matrix classes based on principal pivot transform," Annals of Operations Research, Springer, vol. 243(1), pages 375-382, August.
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