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Projected subgradient techniques and viscosity methods for optimization with variational inequality constraints

机译:具有变分不等式约束的优化投影投影技术和粘度方法

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摘要

In this paper, we propose an easily implementable algorithm in Hilbert spaces for solving some classical monotone variational inequality problem over the set of solutions of mixed variational inequalities. The proposed method combines two strategies: projected subgradient techniques and viscosity-type approximations. The involved stepsizes are controlled and a strong convergence theorem is established under very classical assumptions. Our algorithm can be applied for instance to some mathematical programs with complementarity constraints.
机译:在本文中,我们提出了一种在希尔伯特空间中易于实现的算法,用于解决混合变分不等式解集上的一些经典单调变分不等式问题。所提出的方法结合了两种策略:投影次梯度技术和粘度类型近似。在非常经典的假设下,控制了涉及的步长,并建立了强大的收敛定理。我们的算法可以应用于例如一些具有互补性约束的数学程序。

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