ScholarLens Back to search
2023•RAIRO - Operations ResearchOpen access

Dislocation hyperbolic augmented Lagrangian algorithm for nonconvex optimization

Lennin Mallma Ramirez, Nelson Maculan, Adilson Elias Xavier, Vinícius Layter Xavier

Open full text 11 citations

Abstract

The dislocation hyperbolic augmented Lagrangian algorithm (DHALA) solves the nonconvex programming problem considering an update rule for its penalty parameter and considering a condition to ensure the complementarity condition. in this work, we ensure that the sequence generated by DHALA converges to a Karush-Kuhn-Tucker (KKT) point, and we present computational experiments to demonstrate the performance of our proposed algorithm.

Open-access reader

About this research paper

What this paper is about

The dislocation hyperbolic augmented Lagrangian algorithm (DHALA) solves the nonconvex programming problem considering an update rule for its penalty parameter and considering a condition to ensure the complementarity condition. in this work, we ensure that the sequence generated by DHALA converges to a Karush-Kuhn-Tucker (KKT) point, and we present computational experiments to demonstrate the performance of our proposed algorithm.

Why it matters

OpenAlex reports 11 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The dislocation hyperbolic augmented Lagrangian algorithm (DHALA) solves the nonconvex programming problem considering an update rule for its penalty parameter and considering a condition to ensure the complementarity condition. in this work, we ensure that the sequence generated by DHALA converges to a Karush-Kuhn-Tucker (KKT) point, and we present computational experiments to demonstrate the performance of our proposed algorithm.

Key concepts: Karush–Kuhn–Tucker conditions, Augmented Lagrangian method, Complementarity (molecular biology), Lagrangian, Mathematical optimization, Sequence (biology), Mathematics, Dislocation

Related papers

Related paper 1Related paper 2
Back to paper searchBrowse research topicsOriginal source
Dislocation hyperbolic augmented Lagrangian algorithm for nonconvex optimization — Research Paper | ScholarLens