Self-adaptive gradient projection algorithms for variational inequalities involving non-Lipschitz continuous operators
https://doi.org/10.1007/s11075-018-0578-zPublisher, magazine: ,
Publication year: 2019
Lưu Trích dẫn Chia sẻAbstract
In this paper, we introduce a self-adaptive inertial gradient projection algorithm for solving monotone or strongly pseudomonotone variational inequalities in real Hilbert spaces. The algorithm is designed such that the stepsizes are dynamically chosen and its convergence is guaranteed without the Lipschitz continuity and the paramonotonicity of the underlying operator. We will show that the proposed algorithm yields strong convergence without being combined with the hybrid/viscosity or linesearch methods. Our results improve and develop previously discussed gradient projection-type algorithms by Khanh and Vuong (J. Global Optim. 58, 341–350 2014).
Tags: Variational inequality; Monotone operator; Gradient projection algorithm; Extragradient algorithm; Subgradient extragradient algorithm; Projected reflected gradient method; Inertial-type algorithm.
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