Strong convergence results of two-step inertial projection algorithms for solving variational inequality problem
Abstract
Abstract In this paper, we present and study two strongly convergent two-step inertial accelerated algorithms for solving pseudo-monotone variational inequality problem. Our methods are modification and extension of the Halpern-type method previously studied in the literature. Unique feature of our methods is their ability to handle non-Lipschitz continuous and pseudo-monotone operator through a novel line-search rule. Additionally, the two-step inertial technique incorporated in our methods account for the improvement in the rate of convergence. Finally, we compare our methods with some well-known methods in the literature through numerical experiments. The numerical results reveal that the proposed methods perform better than these methods.
Fields of Study & Subjects
Optimization and Variational Analysis
Stochastic Gradient Optimization Techniques
Advanced Optimization Algorithms Research
Publication details
- Journal / source
- Rendiconti del Circolo Matematico di Palermo Series 2
- Publisher
- Springer Science and Business Media LLC
- Volume
- 75
- Issue
- 2
- Publication date
- 19 January 2026
- Language
- EN