In this work, we construct four efficient multi-step inertial relaxed algorithms based on the monotonic step-length criterion which does not require any information about the norm of the underlying operator or the use of a line search procedure for split feasibility problems in infinite-dimensional Hilbert spaces. The first and the third are the general multi-step inertial-type methods, which unify two steps of the multi-step inertial terms with the golden ratio-based and an alternating golden ratio-based extrapolation steps, respectively, to improve the speed of convergence of their sequences of iterates to a solution of the problem, while the second and the fourth are the three-term conjugate gradient-like and multi-step inertial-type methods, which integrate both the three-term conjugate gradient-like direction and a multi-step inertial term with the golden ratio-based and an alternating golden ratio-based extrapolation steps, respectively, to accelerate their sequences of iterates toward a solution of the problem. Under some simple and weaker assumptions, we formulate and prove some strong convergence theorems for each of these algorithms based on the convergence theorem of a golden ratio-based relaxed algorithm with perturbations and the alternating golden ratio-based relaxed algorithm with perturbations in infinite-dimensional real Hilbert spaces. Moreover, we analyze their applications in classification problems for an interesting real-world dataset based on the extreme learning machine (ELM) with the $\ell_{1}-\ell_{2}$ hybrid regularization approach and in solving constrained minimization problems in infinite-dimensional Hilbert spaces. In all the experiments, our proposed algorithms, which generalizes several algorithms in the literature, comparatively achieve better performance than some related algorithms.
Split feasibility problem Golden ratio algorithm Multi-step inertial method Three-term conjugate gradient method Classification problem
Primary Language | English |
---|---|
Subjects | Mathematical Optimisation, Numerical and Computational Mathematics (Other) |
Journal Section | Research Articles |
Authors | |
Early Pub Date | July 15, 2025 |
Publication Date | June 30, 2025 |
Submission Date | December 3, 2024 |
Acceptance Date | May 12, 2025 |
Published in Issue | Year 2025 Volume: 5 Issue: 2 |