Lennin Mallma Ramirez , Nelson Maculan , Adilson Elias Xavier , Vinicius Layter Xavier
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引用次数: 0
Abstract
In this paper, we study an augmented Lagrangian-type algorithm called the Dislocation Hyperbolic Augmented Lagrangian Algorithm (DHALA), which solves an inequality nonconvex optimization problem. We show that the sequence generated by DHALA converges to a Karush–Kuhn–Tucker (KKT) point under the Mangasarian–Fromovitz constraint qualification. The contribution of our work is to consider a constraint qualification into this algorithm. Finally, we present some computational illustrations to demonstrate the performance our algorithm works.