Title :
The pseudomonotone stochastic variational inequality problem: Analytical statements and stochastic extragradient schemes
Author :
Kannan, Ajaykumar ; Shanbhag, Uday V.
Author_Institution :
Dept. of Ind. & Manuf. Eng., Pennsylvania State Univ., University Park, PA, USA
Abstract :
Variational inequality problems find wide applicability in modeling a range of optimization and equilibrium problems. We consider the stochastic generalization of such a problem wherein the mapping is pseudomonotone and make two sets of contributions in this paper. First, we provide sufficiency conditions for the solvability of such problems that do not require evaluating the expectation. Second, we consider an extragradient variant of stochastic approximation for the solution of such problems and under suitable conditions, show that this scheme produces iterates that converge in an almost-sure sense.
Keywords :
approximation theory; computability; gradient methods; optimisation; stochastic processes; variational techniques; extragradient variant; optimization; pseudomonotone stochastic variational inequality problem; solvability; stochastic approximation; stochastic extragradient schemes; stochastic generalization; sufficiency condition; Approximation methods; Convergence; Educational institutions; Optimization; Standards; Stochastic processes; Vectors; Optimization; Optimization algorithms; Randomized algorithms;
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
Print_ISBN :
978-1-4799-3272-6
DOI :
10.1109/ACC.2014.6859377