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首页> 外文期刊>Journal of Global Optimization >The interior proximal extragradient method for solving equilibrium problems
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The interior proximal extragradient method for solving equilibrium problems

机译:内部近端梯度法求解平衡问题

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In this article we present a new and efficient method for solving equilibrium problems on polyhedra. The method is based on an interior-quadratic proximal term which replaces the usual quadratic proximal term. This leads to an interior proximal type algorithm. Each iteration consists in a prediction step followed by a correction step as in the extragradient method. In a first algorithm each of these steps is obtained by solving an unconstrained minimization problem, while in a second algorithm the correction step is replaced by an Armijo-backtracking linesearch followed by an hyperplane projection step. We prove that our algorithms are convergent under mild assumptions: pseudomonotonicity for the two algorithms and a Lipschitz property for the first one. Finally we present some numerical experiments to illustrate the behavior of the proposed algorithms.
机译:在本文中,我们提出了一种解决多面体平衡问题的新方法。该方法基于内部二次方近端项,它代替了通常的二次二次方近端项。这导致内部近端类型算法。每次迭代都包含一个预测步骤,随后是一个校正步骤,就像超梯度方法一样。在第一种算法中,这些步骤中的每一个都是通过解决无约束最小化问题而获得的,而在第二种算法中,校正步骤是由Armijo回溯线搜索代替,然后是超平面投影步骤。我们证明了我们的算法在温和的假设下是收敛的:两种算法的伪单调性和第一种算法的Lipschitz属性。最后,我们提出了一些数值实验来说明所提出算法的行为。

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