ADMM ALGORITHM FOR TWO BLOCKS NONLINEAR CONSTRAINED NONCONVEX OPTIMIZATION

Shan Zhang; Tong Su; Yaning Zhang

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ADMM ALGORITHM FOR TWO BLOCKS NONLINEAR CONSTRAINED NONCONVEX OPTIMIZATION

机译：两个块非线性约束非convex优化的ADMM算法

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Based on the alternating direction method of multipliers (ADMM), this paper proposes a new efficient algorithm for two blocks nonlinear optimization. Firstly, the nonlinear programming is decomposed into two independent small scale quadratic programming according to ADMM idea. Secondly, the new iteration point of the prime variable is generated by Armijo line search for the augmented Lagrange function. Finally, the dual variables are updated by an explicit expression. Thus, a new ADMM algorithm is constructed. Under the proper conditions, the global convergence of the algorithms is analyzed. Some preliminary numerical results are reported to support the efficiency of the new algorithm.

机译：基于乘数的交替方向方法（ADMM），本文提出了针对两个块非线性优化的新有效算法。首先，根据ADMM的想法，非线性编程被分解为两个独立的小规模二次编程。其次，Prime变量的新迭代点是由Armijo Line搜索增强Lagrange函数生成的。最后，双重变量通过显式表达式更新。因此，构建了一种新的ADMM算法。在适当的条件下，分析了算法的全局收敛性。据报道，一些初步的数值结果支持了新算法的效率。

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《Far east journal of mathematical sciences》 |2021年第1期|47-69|共23页
作者
Shan Zhang; Tong Su; Yaning Zhang;
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作者单位

School of Mathematics and Statistics Changchun University of Technology Changchun, 130022, P. R. China;

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原文格式 PDF
正文语种英语
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关键词
algorithms; Lagrangian; Blocksline retrievalefficient algorithmglobal convergence;

机译：算法;拉格朗日;blocksline检索算法算法收敛;

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ADMM ALGORITHM FOR TWO BLOCKS NONLINEAR CONSTRAINED NONCONVEX OPTIMIZATION

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