[책][B] Uncertainty quantification in variational inequalities: theory, numerics, and applications
Uncertainty Quantification (UQ) is an emerging and extremely active research discipline
which aims to quantitatively treat any uncertainty in applied models. The primary objective of …
which aims to quantitatively treat any uncertainty in applied models. The primary objective of …
Stochastic variational inequalities: single-stage to multistage
Variational inequality modeling, analysis and computations are important for many
applications, but much of the subject has been developed in a deterministic setting with no …
applications, but much of the subject has been developed in a deterministic setting with no …
Stochastic variational inequalities: residual minimization smoothing sample average approximations
The stochastic variational inequality (VI) has been used widely in engineering and
economics as an effective mathematical model for a number of equilibrium problems …
economics as an effective mathematical model for a number of equilibrium problems …
[PDF][PDF] Stochastic equilibrium problems and stochastic mathematical programs with equilibrium constraints: A survey
In the recent optimization research community, various equilibrium problems and related
problems under uncertainty have drawn increasing attention. Novel formulations and …
problems under uncertainty have drawn increasing attention. Novel formulations and …
Two-stage stochastic variational inequalities: an ERM-solution procedure
We propose a two-stage stochastic variational inequality model to deal with random
variables in variational inequalities, and formulate this model as a two-stage stochastic …
variables in variational inequalities, and formulate this model as a two-stage stochastic …
Two-stage stochastic variational inequalities: theory, algorithms and applications
The stochastic variational inequality (SVI) provides a unified form of optimality conditions of
stochastic optimization and stochastic games which have wide applications in science …
stochastic optimization and stochastic games which have wide applications in science …
The scenario approach meets uncertain game theory and variational inequalities
Variational inequalities are modeling tools used to capture a variety of decision-making
problems arising in mathematical optimization, operations research, game theory. The …
problems arising in mathematical optimization, operations research, game theory. The …
An infeasible stochastic approximation and projection algorithm for stochastic variational inequalities
XJ Zhang, XW Du, ZP Yang, GH Lin - Journal of Optimization Theory and …, 2019 - Springer
In this paper, we consider a stochastic variational inequality, in which the map** involved
is an expectation of a given random function. Inspired by the work of He (Appl Math Optim …
is an expectation of a given random function. Inspired by the work of He (Appl Math Optim …
Two-stage stochastic variational inequality arising from stochastic programming
M Li, C Zhang - Journal of Optimization Theory and Applications, 2020 - Springer
We consider a two-stage stochastic variational inequality arising from a general convex two-
stage stochastic programming problem, where the random variables have continuous …
stage stochastic programming problem, where the random variables have continuous …
Convergence results of the ERM method for nonlinear stochastic variational inequality problems
MJ Luo, GH Lin - Journal of optimization theory and applications, 2009 - Springer
This paper considers the expected residual minimization (ERM) method proposed by Luo
and Lin (J. Optim. Theory Appl. 140: 103–116, 2009) for a class of stochastic variational …
and Lin (J. Optim. Theory Appl. 140: 103–116, 2009) for a class of stochastic variational …