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PERIODIC SYSTEMS WITH TIME DEPENDENT MAXIMAL MONOTONE OPERATORS
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作者 Zhenhai LIU Nikolaos S.PAPAGEORGIOU 《Acta Mathematica Scientia》 SCIE CSCD 2024年第4期1280-1300,共21页
We consider a first order periodic system in R^(N),involving a time dependent maximal monotone operator which need not have a full domain and a multivalued perturbation.We prove the existence theorems for both the con... We consider a first order periodic system in R^(N),involving a time dependent maximal monotone operator which need not have a full domain and a multivalued perturbation.We prove the existence theorems for both the convex and nonconvex problems.We also show the existence of extremal periodic solutions and provide a strong relaxation theorem.Finally,we provide an application to nonlinear periodic control systems. 展开更多
关键词 periodic boundary condition time-dependent maximal monotone operator convex and nonconvex problems extremal solutions strong relaxation
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A GENERAL TWO-LEVEL SUBSPACE METHOD FOR NONLINEAR OPTIMIZATION
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作者 Cheng Chen Zaiwen Wen Yaxiang Yuan 《Journal of Computational Mathematics》 SCIE CSCD 2018年第6期881-902,共22页
A new two-level subspace method is proposed for solving the general unconstrained minimization formulations discretized from infinite-dimensional optimization problems. At each iteration, the algorithm executes either... A new two-level subspace method is proposed for solving the general unconstrained minimization formulations discretized from infinite-dimensional optimization problems. At each iteration, the algorithm executes either a direct step on the current level or a coarse subspace correction step. In the coarse subspace correction step, we augment the traditional coarse grid space by a two-dimensional subspace spanned by the coordinate direction and the gradient direction at the current point. Global convergence is proved and convergence rate is studied under some mild conditions on the discretized functions. Preliminary numerical experiments on a few variational problems show that our two-level subspace method is promising. 展开更多
关键词 Nonlinear optimization convex and nonconvex problems Subspace technique Multigrid/multilevel method Large-scale problems
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