非凸优化的位错双曲增广拉格朗日算法

IF 1.8 4区管理学 Q3 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Rairo-Operations Research Pub Date : 2023-09-01 DOI:10.1051/ro/2023153

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

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引用次数: 0

摘要

位错双曲增广拉格朗日算法(DHALA)考虑了惩罚参数的更新规则和保证互补条件，解决了非凸规划问题。在这项工作中，我们确保由DHALA生成的序列收敛到一个Karush-Kuhn-Tucker (KKT)点，并通过计算实验来证明我们提出的算法的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Dislocation hyperbolic augmented Lagrangian algorithm for nonconvex optimization

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.

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来源期刊

Rairo-Operations Research 管理科学-运筹学与管理科学

CiteScore

3.60

自引率

22.20%

发文量

206

审稿时长

>12 weeks

期刊介绍： RAIRO-Operations Research is an international journal devoted to high-level pure and applied research on all aspects of operations research. All papers published in RAIRO-Operations Research are critically refereed according to international standards. Any paper will either be accepted (possibly with minor revisions) either submitted to another evaluation (after a major revision) or rejected. Every effort will be made by the Editorial Board to ensure a first answer concerning a submitted paper within three months, and a final decision in a period of time not exceeding six months.