Strong convergence of inertial projection and contraction methods for pseudomonotone variational inequalities with applications to optimal control problems

DOI10.1007/s10898-021-01095-yzbMath1497.47100OpenAlexW3202469102MaRDI QIDQ2114596

Xiaolong Qin, Bing Tan, Jen-Chih Yao

Publication date: 15 March 2022

Published in: Journal of Global Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10898-021-01095-y

zbMATH Keywords

strong convergenceoptimal control problemLipschitz constantvariational inequality problemreal Hilbert spacespseudomonotone mappingprojection and contraction methodsubgradient extragradient methodinertial method

Mathematics Subject Classification ID

Variational and other types of inequalities involving nonlinear operators (general) (47J20) Monotone operators and generalizations (47H05) Iterative procedures involving nonlinear operators (47J25) Contraction-type mappings, nonexpansive mappings, (A)-proper mappings, etc. (47H09) Existence theories for optimal control problems involving ordinary differential equations (49J15) Numerical methods for variational inequalities and related problems (65K15)

Related Items (6)

A modified subgradient extragradient algorithm-type for solving quasimonotone variational inequality problems with applications ⋮ A modified generalized version of projected reflected gradient method in Hilbert spaces ⋮ Modified inertial projection and contraction algorithms with non-monotonic step sizes for solving variational inequalities and their applications ⋮ Strong convergence of forward-reflected-backward splitting methods for solving monotone inclusions with applications to image restoration and optimal control ⋮ Two-step inertial forward-reflected-anchored-backward splitting algorithm for solving monotone inclusion problems ⋮ Strongly convergent inertial forward-backward-forward algorithm without on-line rule for variational inequalities

Uses Software

• FOM

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