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首页> 外文期刊>Journal of Optimization Theory and Applications >An Inexact Modified Subgradient Algorithm for Primal-Dual Problems via Augmented Lagrangians
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An Inexact Modified Subgradient Algorithm for Primal-Dual Problems via Augmented Lagrangians

机译:扩展拉格朗日算子的原始对偶问题的不精确修正次梯度算法

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We consider a primal optimization problem in a reflexive Banach space and a duality scheme via generalized augmented Lagrangians. For solving the dual problem (in a Hilbert space), we introduce and analyze a new parameterized Inexact Modified Subgradient (IMSg) algorithm. The IMSg generates a primal-dual sequence, and we focus on two simple new choices of the stepsize. We prove that every weak accumulation point of the primal sequence is a primal solution and the dual sequence converges weakly to a dual solution, as long as the dual optimal set is nonempty. Moreover, we establish primal convergence even when the dual optimal set is empty. Our second choice of the stepsize gives rise to a variant of IMSg which has finite termination.
机译:我们考虑了自反Banach空间中的原始优化问题,以及通过广义增强拉格朗日方程的对偶方案。为了解决对偶问题(在希尔伯特空间中),我们引入并分析了一种新的参数化不精确修饰子梯度(IMSg)算法。 IMSg生成原始对偶序列,并且我们关注逐步大小的两个简单的新选择。我们证明,只要对偶最优集是非空的,原始序列的每个弱累加点都是原始解,并且对偶序列弱地收敛到对偶解。此外,即使对偶最优集为空,我们也会建立原始收敛。我们对步长的第二种选择产生了具有有限端接的IMSg变体。

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