Superiorization and bounded perturbation resilience of a gradient projection algorithm solving the convex minimization problem

In this article, we use the superiorization methodology to investigate the bounded perturbations resilience of the gradient projection algorithm proposed in Ertürk et al. (J Nonlinear Convex Anal 21(4):943–951, 2020) for solving the convex minimization problem in Hilbert space setting. We obtain tha...

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Veröffentlicht in:	Optimization letters Jg. 17; H. 8; S. 1957 - 1978
Hauptverfasser:	Ertürk, Müzeyyen, Salkım, Ahmet
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2023
Schlagworte:	Computational Intelligence Mathematics Mathematics and Statistics Numerical and Computational Physics Operations Research/Decision Theory Optimization Original Paper Simulation Gradient projection algorithm Bounded perturbation resilience Convex minimization problems Linear inverse problems Superiorization Split feasibility problems
ISSN:	1862-4472, 1862-4480
Online-Zugang:	Volltext
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