Work

A Self-adaptive Super Set-relaxed Projection Method for Multiple-sets Split Feasibility Problem with Multiple Output Sets

Year: 2024

Type: article

Abstract: This paper introduces an inertial accelerated super set-relaxed CQ method to solve a multiple-sets split feasibility problem with multiple output sets. The convex subsets involved are assumed to be level subsets of given strongly convex functions. Instead of using the involved sets, we approximate the original convex subsets with a sequence of closed balls. The proposed method is easy to implement as the projection onto the closed ball has a closed form. Additionally, we develop a new self-adaptive step-size that does not require any prior information of the norm. Under suitable assumptions, we establish and prove a strong convergence result for the algorithm. Numerical experiments are provided to demonstrate the performance of the proposed algorithm, which generalizes and improves upon existing literature.

Source: Nonlinear Convex Analysis and Optimization: An International Journal on Numerical, Computation and Applications

DOI: 10.58715/ncao.2024.3.4

Authors: Guash Haile Taddele, Songpon Sriwongsa, Attapol Kaewkhao

Institutions: Xiamen University Malaysia, King Mongkut's University of Technology Thonburi, Chiang Mai University

Language: English

Topic: Optimization and Variational Analysis

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: Chiang Mai University, King Mongkut's University of Technology Thonburi, Xiamen University, Thailand Science Research and Innovation

Awards: G2858001283, G642137015