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首页> 外文期刊>Optimization Letters >Self adaptive inertial subgradient extragradient algorithms for solving pseudomonotone variational inequality problems
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Self adaptive inertial subgradient extragradient algorithms for solving pseudomonotone variational inequality problems

机译:自适应惯性子底肾异质算法,用于求解假鼠变分不等式问题

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摘要

In this paper, two new algorithms are introduced for solving a pseudomontone variational inequality problem with a Lipschitz condition in a Hilbert space. The algorithms are constructed around three methods: the subgradient extragradient method, the inertial method and the viscosity method. With a new stepsize rule is incorporated, the algorithms work without any information of Lipschitz constant of operator. The weak convergence of the first algorithm is established, while the second one is strongly convergent which comes from the viscosity method. In order to show the computational effectiveness of our algorithms, some numerical results are provided.
机译:在本文中,引入了两种新算法,用于解决Hilbert空间中的Lipschitz条件的假表断变分性不等式问题。 该算法围绕三种方法构建:子辐射型异构法,惯性方法和粘度法。 结合了新的步骤化规则,算法在没有操作员的嘴唇常数的任何信息的情况下工作。 建立了第一算法的弱收敛,而第二个是来自粘度法的强烈收敛。 为了显示我们算法的计算效率,提供了一些数值结果。

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