
handle: 2078.1/4560 , 20.500.11769/39289
In this paper we develop a new and efficient method for variational inequality with Lipschitz continuous strongly monotone operator. Our analysis is based on a new strongly convex merit function. We apply a variant of the developed scheme for solving quasivariational inequality. As a result, we significantly improve the standard sufficient condition for existence and uniqueness of their solutions. Moreover, we get a new numerical scheme, which rate of convergence is much higher than that of the straightforward gradient method.
Variational inequality, Variational inequality; monotone operators; complexity analysis, variational inequality, quasivariational inequality, monotone operators, complexity analysis, efficiency estimate, optimal methods, Quasivariational inequality, Monotone operators, Efficiency estimate, Optimal methods, Complexity analysis
Variational inequality, Variational inequality; monotone operators; complexity analysis, variational inequality, quasivariational inequality, monotone operators, complexity analysis, efficiency estimate, optimal methods, Quasivariational inequality, Monotone operators, Efficiency estimate, Optimal methods, Complexity analysis
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 68 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
