Expected Residual Minimization Formulation for a Class of Stochastic Vector Variational Inequalities |
| |
Authors: | Yong Zhao Jin Zhang Xinmin Yang Gui-Hua Lin |
| |
Affiliation: | 1.Department of Mathematics,Sichuan University,Chengdu,China;2.Department of Mathematics,Hong Kong Baptist University,Hongkong,China;3.Department of Mathematics,Chongqing Normal University,Chongqing,China;4.School of Management,Shanghai University,Shanghai,China |
| |
Abstract: | This paper considers a class of vector variational inequalities. First, we present an equivalent formulation, which is a scalar variational inequality, for the deterministic vector variational inequality. Then we concentrate on the stochastic circumstance. By noting that the stochastic vector variational inequality may not have a solution feasible for all realizations of the random variable in general, for tractability, we employ the expected residual minimization approach, which aims at minimizing the expected residual of the so-called regularized gap function. We investigate the properties of the expected residual minimization problem, and furthermore, we propose a sample average approximation method for solving the expected residual minimization problem. Comprehensive convergence analysis for the approximation approach is established as well. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|