错位双曲增强拉格朗日算法的约束条件

Lennin Mallma Ramirez , Nelson Maculan , Adilson Elias Xavier , Vinicius Layter Xavier
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引用次数: 0

摘要

本文研究了一种称为 "位错双曲增强拉格朗日算法(DHALA)"的增强拉格朗日类型算法,该算法用于解决不等式非凸优化问题。我们证明,在 Mangasarian-Fromovitz 约束条件下,DHALA 生成的序列会收敛到 Karush-Kuhn-Tucker (KKT) 点。我们工作的贡献在于将约束条件考虑到了这一算法中。最后,我们给出了一些计算示例,以展示我们算法的工作性能。
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A constraint qualification for the dislocation hyperbolic augmented Lagrangian algorithm

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.

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来源期刊
Results in Control and Optimization
Results in Control and Optimization Mathematics-Control and Optimization
CiteScore
3.00
自引率
0.00%
发文量
51
审稿时长
91 days
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