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。

查看原文本刊更多论文

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.