Summary.
Bermúdez-Moreno [5] presents a duality numerical algorithm for solving variational inequalities of the second kind. The performance of this algorithm strongly depends on the choice of two constant parameters. Assuming a further hypothesis of the inf-sup type, we present here a convergence theorem that improves on the one presented in [5]: we prove that the convergence is linear, and we give the expression of the asymptotic error constant and the explicit form of the optimal parameters, as a function of some constants related to the variational inequality. Finally, we present some numerical examples that confirm the theoretical results.
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Received June 28, 1999 / Revised version received February 19, 2001 / Published online October 17, 2001
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Parés, C., Castro, M. & Macías, J. On the convergence of the Bermúdez-Moreno algorithm with constant parameters. Numer. Math. 92, 113–128 (2002). https://doi.org/10.1007/s002110100352
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DOI: https://doi.org/10.1007/s002110100352