Regularization method and a posteriori error estimates for the bilateral obstacle problem

In this paper, we present a relatively complete analysis of the regularization method for of the bilateral obstacle problem with a non-homogeneous condition on the boundary. We provide both the convergence result and a priori estimates. Then by the duality theory from the convex analysis, we determine the dual problem associated with the of the bilateral obstacle problem. Based on this dual problem, we provide a posteriori error estimates for the continuous and the discrete problems. The a posteriori error estimates are desired for the practical implementation of the regularized problem.

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Publication Details

Journal
Gulf Journal of Mathematics
Published
2024-09-22
DOI
https://doi.org/10.56947/gjom.v17i2.2162
Citations
1
Primary Topic
Numerical methods in inverse problems
Type
article
Field-Weighted Citation Impact
0.89
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article

Regularization method and a posteriori error estimates for the bilateral obstacle problem

Mohammed Bouchlaghem, Zhor Mellah, El Bekkay Mermri
1 citations
Gulf Journal of Mathematics
Numerical methods in inverse problems
0.89
article

Regularization method and a posteriori error estimates for the bilateral obstacle problem

Mohammed Bouchlaghem, Zhor Mellah, El Bekkay Mermri
article en
1 citations

Abstract

In this paper, we present a relatively complete analysis of the regularization method for of the bilateral obstacle problem with a non-homogeneous condition on the boundary. We provide both the convergence result and a priori estimates. Then by the duality theory from the convex analysis, we determine the dual problem associated with the of the bilateral obstacle problem. Based on this dual problem, we provide a posteriori error estimates for the continuous and the discrete problems. The a posteriori error estimates are desired for the practical implementation of the regularized problem.

Gulf Journal of MathematicsVol. 17(2)
Premier University (BD)
Reduced inequalities
Openalex Percentile: Top 29%
Numerical methods in inverse problems
0.89
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