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2015 Volume 40 Issue 8
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YIN Yu. On a Proximal Point Algorithm for Solving a Class of Nonconvex Variational Inequalities[J]. Journal of Southwest China Normal University(Natural Science Edition), 2015, 40(8).
Citation: YIN Yu. On a Proximal Point Algorithm for Solving a Class of Nonconvex Variational Inequalities[J]. Journal of Southwest China Normal University(Natural Science Edition), 2015, 40(8).

On a Proximal Point Algorithm for Solving a Class of Nonconvex Variational Inequalities

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  • T his paper introduces and considers a new class of nonconvex variational inequalities .T his class of variational inequalities includes some know n and new nonconvex variational inequalities as special cases . Relying on the γ‐prox‐regularity notion ,we have established the equivalence between the variational ine‐qualities and the fixed point problems .By means of the equivalence ,we suggest and analyze a proximal point algorithm for solving this nonconvex variational inequalities .The new algorithm converges under certain mild conditions .As a consequence ,the algorithm and results presented in the paper overcome incor‐rect algorithms and results existing in the literature [1] .Our results can also be viewed as a novel and im‐portant extension and improvement of the previously known results .
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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On a Proximal Point Algorithm for Solving a Class of Nonconvex Variational Inequalities

Abstract: T his paper introduces and considers a new class of nonconvex variational inequalities .T his class of variational inequalities includes some know n and new nonconvex variational inequalities as special cases . Relying on the γ‐prox‐regularity notion ,we have established the equivalence between the variational ine‐qualities and the fixed point problems .By means of the equivalence ,we suggest and analyze a proximal point algorithm for solving this nonconvex variational inequalities .The new algorithm converges under certain mild conditions .As a consequence ,the algorithm and results presented in the paper overcome incor‐rect algorithms and results existing in the literature [1] .Our results can also be viewed as a novel and im‐portant extension and improvement of the previously known results .

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