Convergence analysis of a mixed logarithmic barrier-augmented Lagrangian algorithm without constraint qualification.
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| Title: | Convergence analysis of a mixed logarithmic barrier-augmented Lagrangian algorithm without constraint qualification. |
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| Authors: | Nguyen, Tran Ngoc1 (AUTHOR) tranngocnguyen@qnu.edu.vn |
| Source: | Computational Optimization & Applications. Jul2025, Vol. 91 Issue 3, p1105-1134. 30p. |
| Subjects: | Constraint algorithms, Lagrangian points, Jacobian matrices, Constraint programming, Nonlinear programming |
| Abstract: | In this paper, we exploit some properties of points in a neighborhood of the solution set of degenerate optimization problems. Combining these facts with the boundedness of the inverse of regularized Jacobian matrix arising in a mixed logarithmic barrier-augmented lagrangian method, we propose an updating rule for parameters of a mixed logarithmic barrier-augmented Lagrangian algorithm. The superlinear convergence of this algorithm is then proved without any constraint qualification. Numerical results on degenerate problems are also presented to confirm theoretical results. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | In this paper, we exploit some properties of points in a neighborhood of the solution set of degenerate optimization problems. Combining these facts with the boundedness of the inverse of regularized Jacobian matrix arising in a mixed logarithmic barrier-augmented lagrangian method, we propose an updating rule for parameters of a mixed logarithmic barrier-augmented Lagrangian algorithm. The superlinear convergence of this algorithm is then proved without any constraint qualification. Numerical results on degenerate problems are also presented to confirm theoretical results. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 09266003 |
| DOI: | 10.1007/s10589-025-00690-z |
