Bounded Perturbation Resilience and Superiorization of Proximal Scaled Gradient Algorithm with Multi-Parameters

Yanni Guo and Xiaozhi Zhao
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Yanni Guo: College of Science, Civil Aviation University of China, Tianjin 300300, China
Xiaozhi Zhao: College of Science, Civil Aviation University of China, Tianjin 300300, China

Mathematics, 2019, vol. 7, issue 6, 1-14

Abstract: In this paper, a multi-parameter proximal scaled gradient algorithm with outer perturbations is presented in real Hilbert space. The strong convergence of the generated sequence is proved. The bounded perturbation resilience and the superiorized version of the original algorithm are also discussed. The validity and the comparison with the use or not of superiorization of the proposed algorithms were illustrated by solving the l 1 − l 2 problem.

Keywords: strong convergence; proximal scaled gradient algorithm; multi-parameter; superiorization; convex minimization problem (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
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