نتایج جستجو برای: lipschitzian mapping

تعداد نتایج: 198887  

Journal: :SIAM Journal on Optimization 2007
María J. Cánovas Diethard Klatte Marco A. López Juan Parra

This paper is concerned with the Lipschitzian behavior of the optimal set of convex semi-infinite optimization problems under continuous perturbations of the right hand side of the constraints and linear perturbations of the objective function. In this framework we provide a sufficient condition for the metric regularity of the inverse of the optimal set mapping. This condition consists of the ...

2007
R. T. Rockafellar

Proximal mappings, which generalize projection mappings, were introduced by Moreau and shown to be valuable in understanding the subgradient properties of convex functions. Proximal mappings subsequently turned out to be important also in numerical methods of optimization and the solution of nonlinear partial differential equations and variational inequalities. Here it is shown that, when a con...

Journal: :Mathematics 2023

In this paper, under some new appropriate conditions imposed on the parameters and mappings involved in proximal mapping associated with a general H-monotone operator, its Lipschitz continuity is proved an estimate of constant computed. The main contribution work establishment equivalence relationship between graph convergence sequence strongly their mappings, respectively, to given by using no...

2007
V. Jeyakumar

In this paper, three key theorems (the open mapping theorem, the inverse function theorem, and the implicit function theorem) for continuously differentiable maps are shown to hold for nonsmooth continuous maps which are not necessarily Lipschitz continuous. The significance of these extensions is that they are given using generalized Jacobians, called approximate Jacobians. The approximate Jac...

2006
Lin Wang Nan-Jing Huang

In real Hilbert spaceH , from an arbitrary initial point x0 ∈H , an explicit iteration scheme is defined as follows: xn+1 = αnxn + (1 − αn)Tn+1xn,n ≥ 0, where Tn+1xn = Txn − λn+1μF(Txn), T :H →H is a nonexpansive mapping such that F(T) = {x ∈ K : Tx = x} is nonempty, F :H →H is a η-strongly monotone and k-Lipschitzian mapping, {αn} ⊂ (0,1), and {λn} ⊂ [0,1). Under some suitable conditions, the ...

2012
Wataru Takahashi Ngai-Ching Wong Jen-Chih Yao

Let H be a real Hilbert space, and let C be a nonempty closed convex subset of H. Let α > 0, and let A be an α-inverse strongly-monotone mapping of C into H. Let T be a generalized hybrid mapping of C into H. Let B andW be maximal monotone operators on H such that the domains of B andW are included in C. Let 0 < k < 1, and let g be a k-contraction of H into itself. Let V be a γ -strongly monoto...

Journal: :SIAM Journal on Optimization 2010
Rafael Correa Pedro Gajardo Lionel Thibault

In this work we introduce for extended real valued functions, defined on a Banach space X, the concept of K directionally Lipschitzian behavior, where K is a bounded subset of X. For different types of sets K (e.g., zero, singleton, or compact), the K directionally Lipschitzian behavior recovers well-known concepts in variational analysis (locally Lipschitzian, directionally Lipschitzian, or co...

2009
SHAHRAM SAEIDI

We show that the variational inequality V I(C,A) has a unique solution for a relaxed (γ, r)-cocoercive, μ-Lipschitzian mapping A : C → H with r > γμ, where C is a nonempty closed convex subset of a Hilbert space H . From this result, it can be derived that, for example, the recent algorithms given in the references of this paper, despite their becoming more complicated, are not general as they ...

2005
L. C. Zeng N. C. Wong J. C. Yao Bingren Li

Let C be a nonempty closed convex subset of a real Banach space E. Let S : C → C be a quasi-nonexpansive mapping, let T : C → C be an asymptotically demicontractive and uniformly Lipschitzian mapping, and let F := {x ∈ C : Sx = x and Tx = x} 6 = ∅. Let {xn}n≥0 be the sequence generated from an arbitrary x0 ∈ C by xn+1 = (1− cn)Sxn + cnT xn, n ≥ 0. We prove necessary and sufficient conditions fo...

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