About the Kernel of the strongly quasiconvex function generated projection

This paper explores a natural generalization of Euclidean projection through the lens of strongly quasiconvex functions, as developed in prior works. By establishing a connection between strongly quasiconvex functions and the theory of mutually polar mappings on convex cones, we integrate this generalized projection concept into the duality framework of Riesz spaces, vector norms, and Euclidean metric projections. A central result of this study is the identification of conditions under which the null space of a projection onto a closed convex cone forms a closed convex cone. We provide a comprehensive characterization of such cones and projections, highlighting their fundamental role in extending the duality theory to generalized projection operators.

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Publication Details

Journal
Optimization
Published
2025-11-21
DOI
https://doi.org/10.1080/02331934.2025.2591211
Primary Topic
Optimization and Variational Analysis
Type
article
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article

About the Kernel of the strongly quasiconvex function generated projection

S. Z. Németh, A. B. Németh
Optimization
Optimization and Variational Analysis
article

About the Kernel of the strongly quasiconvex function generated projection

S. Z. Németh, A. B. Németh
article en

Abstract

This paper explores a natural generalization of Euclidean projection through the lens of strongly quasiconvex functions, as developed in prior works. By establishing a connection between strongly quasiconvex functions and the theory of mutually polar mappings on convex cones, we integrate this generalized projection concept into the duality framework of Riesz spaces, vector norms, and Euclidean metric projections. A central result of this study is the identification of conditions under which the null space of a projection onto a closed convex cone forms a closed convex cone. We provide a comprehensive characterization of such cones and projections, highlighting their fundamental role in extending the duality theory to generalized projection operators.

Optimization
Babeș-Bolyai University (RO), University of Birmingham (GB)
Openalex Percentile: Top 64%
Optimization and Variational Analysis
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