The multistage stochastic variational inequality is reformulated equivalently into a variational inequality with separable structure through introducing a new variable. Two classes of splitting algorithms, which are originally used to solve deterministic variational inequalities with separable structure, are used to solve the multistage stochastic variational inequalities. The weak convergence of those algorithms is proved under the assumptions of monotonicity and Lipschitz continuity.

报告人简介

张海森，四川师范大学数学科学学院教授，博士生导师，主要研究领域为随机最优控制。目前主持和参与国家自然科学基金项目 3 项，在 SIAM Review, Transactions of the American Mathematical Society, SIAM Journal on Control and Optimization, Journal of Differential Equations 等期刊发表 SCI 学术论文 12 篇。其中，与四川大学张旭教授合作关于随机最优控制二阶逐点型必要条件的研究工作被美国工业与应用数学会评选为“SIGEST”论文。