Improved convergence order for augmented penalty algorithms

Dussault JP

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Improved convergence order for augmented penalty algorithms

机译：增强惩罚算法的改进收敛阶

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摘要

We refine the speed of convergence analysis for the quadratic augmented penalty algorithm. We improve the convergence order from 4/3 to 3/2 for the first order multiplier iteration. For the second order iteration, we generalize the analysis, and consider a primal-dual variant which asymptotically reduces to a Newton step for the optimality conditions.

机译：我们改进了二次增罚算法的收敛性分析速度。对于一阶乘法器迭代，我们将收敛阶数从4/3提高到3/2。对于二阶迭代，我们对分析进行了概括，并考虑了最优最优条件渐近地减少到牛顿阶跃的原始对偶变体。

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《Computational optimization and applications》 |2009年第3期|共11页
作者
Dussault JP;
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正文语种 eng
中图分类最优化的数学理论;
关键词
Augmented Lagrangian; Augmented penalty; Asymptotic convergence order;

机译：拉格朗日增广惩罚度渐近收敛阶;

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Improved convergence order for augmented penalty algorithms

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