Dislocation hyperbolic augmented Lagrangian algorithm in convex programming

Dislocation hyperbolic augmented Lagrangian algorithm in convex programming

The dislocation hyperbolic augmented Lagrangian algorithm (DHALA) is a new approach to the hyperbolic augmented Lagrangian algorithm (HALA). DHALA is designed to solve convex nonlinear programming problems. We guarantee that the sequence generated by DHALA converges towards a Karush-Kuhn-Tucker poin...

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Veröffentlicht in:An international journal of optimization and control 2024-01, Vol.14 (2), p.147-155
Hauptverfasser: Mallma Ramirez, Lennin, Maculan, Nelson, Elias Xavier, Adilson, Layter Xavier, Vinicius
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Augmented Lagrangian
Computer science
constrained optimization
convergence
convex problem
Convexity
Mathematical functions
Mathematical programming
Nonlinear programming
Optimization
Science programs
Systems engineering
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Zusammenfassung:The dislocation hyperbolic augmented Lagrangian algorithm (DHALA) is a new approach to the hyperbolic augmented Lagrangian algorithm (HALA). DHALA is designed to solve convex nonlinear programming problems. We guarantee that the sequence generated by DHALA converges towards a Karush-Kuhn-Tucker point. We are going to observe that DHALA has a slight computational advantage in solving the problems over HALA. Finally, we will computationally illustrate our theoretical results.
ISSN:2146-0957
2146-5703
DOI:10.11121/ijocta.1402