A Novel Accelerated Parallel Shrinking Projection Regularized Splitting Algorithm for Solving Generalized Split Monotone Variational Inclusion Problems

This paper introduces a novel parallel hybrid algorithm, based on an accelerated shrinking projection method, for solving the Split Monotone Variational Inclusion problems with multiple output sets in Hilbert spaces. Under an appropriate set of conditions, we establish the strong convergence of the proposed algorithm. Its practical viability is further demonstrated through a numerical experiment. The results obtained herein generalize and improve upon several existing findings in the literature.

Authors

Institutions

Publication Details

Journal
Journal of convex analysis
Published
2026-10-30
DOI
https://doi.org/10.68381/jca34014
Primary Topic
Optimization and Variational Analysis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Novel Accelerated Parallel Shrinking Projection Regularized Splitting Algorithm for Solving Generalized Split Monotone Variational Inclusion Problems

Yasir Arfat
3 links
Journal of convex analysis
Optimization and Variational Analysis
article

A Novel Accelerated Parallel Shrinking Projection Regularized Splitting Algorithm for Solving Generalized Split Monotone Variational Inclusion Problems

Yasir Arfat
article en

Abstract

This paper introduces a novel parallel hybrid algorithm, based on an accelerated shrinking projection method, for solving the Split Monotone Variational Inclusion problems with multiple output sets in Hilbert spaces. Under an appropriate set of conditions, we establish the strong convergence of the proposed algorithm. Its practical viability is further demonstrated through a numerical experiment. The results obtained herein generalize and improve upon several existing findings in the literature.

Journal of convex analysisVol. 34(1)
Universidade de São Paulo (BR)
Fundação de Amparo à Pesquisa do Estado de São Paulo
Openalex Percentile: Top 14%
Optimization and Variational Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon