A double inertial method for non-monotone variational inequality problem

Abstract In this paper, we propose a viscosity-type double inertial algorithm with self-adaptive stepsizes for solving non-monotone variational inequality problems involving uniformly continuous operators in real Hilbert spaces. The proposed method combines viscosity approximation and double inertial extrapolation techniques with a self-adaptive stepsize rule that does not require prior knowledge of the Lipschitz constant. Under suitable conditions, we establish a strong convergence of the generated sequence without assuming monotonicity, Lipschitz continuity, line-search procedures, or additional projection techniques. The obtained results extend several existing inertial and viscosity methods to a broader class of non-monotone and non-Lipschitz variational inequality problems. Numerical examples are presented to illustrate the effectiveness of the proposed algorithm.

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Publication Details

Journal
ANNALI DELL UNIVERSITA DI FERRARA
Published
2026-10-17
DOI
https://doi.org/10.1007/s11565-026-00776-4
Primary Topic
Optimization and Variational Analysis
Type
article
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article

A double inertial method for non-monotone variational inequality problem

Austine Efut Ofem, Ojen Kumar Narain, Chinedu Izuchukwu, Olayinka Martins Onifade et al.
ANNALI DELL UNIVERSITA DI FERRARA
Optimization and Variational Analysis
article

A double inertial method for non-monotone variational inequality problem

Austine Efut Ofem, Ojen Kumar Narain, Chinedu Izuchukwu, Olayinka Martins Onifade, S. A. Kajola
article en

Abstract

Abstract In this paper, we propose a viscosity-type double inertial algorithm with self-adaptive stepsizes for solving non-monotone variational inequality problems involving uniformly continuous operators in real Hilbert spaces. The proposed method combines viscosity approximation and double inertial extrapolation techniques with a self-adaptive stepsize rule that does not require prior knowledge of the Lipschitz constant. Under suitable conditions, we establish a strong convergence of the generated sequence without assuming monotonicity, Lipschitz continuity, line-search procedures, or additional projection techniques. The obtained results extend several existing inertial and viscosity methods to a broader class of non-monotone and non-Lipschitz variational inequality problems. Numerical examples are presented to illustrate the effectiveness of the proposed algorithm.

ANNALI DELL UNIVERSITA DI FERRARAVol. 72(4)
Tshwane University of Technology (ZA), University of the Witwatersrand (ZA), University of KwaZulu-Natal (ZA)
Openalex Percentile: Top 14%
Optimization and Variational Analysis
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