Let (E, ρ) be a metric space and K be a nonempty subset of E. For every x∊E, the distance between the point x and K is denoted by ρ(x, K) and is defined by the following minimum problem: \(\rho {\rm{(}}x{\rm{,}}K{\rm{) : = }}\mathop {{\rm{inf}}}\limits_{y \in K} {\rm{ }}\rho {\rm{(}}x{\rm{,}}y{\rm{)}}{\rm{.}}\) The metric projection operator (also called the nearest point mapping) Pk defined on E is a mapping from E to 2K such that \(P_K {\rm{(}}x{\rm{) : = \{ }}z{\rm{ }} \in {\rm{ }}K{\rm{ : }}\rho {\rm{(}}x{\rm{, }}z{\rm{) = }}\rho {\rm{(}}x{\rm{,}}K{\rm{)\} }}\forall {\rm{ }}x{\rm{ }} \in {\rm{ }}E{\rm{.}}\).
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© 2009 Springer-Verlag Berlin Heidelberg
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(2009). Hybrid Steepest Descent Method for Variational Inequalities. In: Geometric Properties of Banach Spaces and Nonlinear Iterations. Lecture Notes in Mathematics, vol 1965. Springer, London. https://doi.org/10.1007/978-1-84882-190-3_7
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