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Duality in convex optimization for the hyperbolic augmented Lagrangian

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

摘要

We guarantee the strong duality and the existence of a saddle point of the hyperbolic augmented Lagrangian function (HALF) in convex optimization. To guarantee these results, we assume a set of convexity hypothesis and the Slater condition. Finally, we computationally illustrate our theoretical results obtained in this work.