An International Journal of Optimization and Control: Theories & Applications (Apr 2024)

Dislocation hyperbolic augmented Lagrangian algorithm in convex programming

  • Lennin Mallma Ramirez,
  • Nelson Maculan,
  • Adilson Elias Xavier,
  • Vinicius Layter Xavier

DOI
https://doi.org/10.11121/ijocta.1402
Journal volume & issue
Vol. 14, no. 2

Abstract

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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.

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