报告主题：不确定条件下随机变分不等式及最优化
报告人：孙捷 教授 （澳大利亚 Curtin University 数学系）
报告时间：2019年6月3日（周一） 10：30
报告地点：校本部G507
邀请人：余长君副教授
报告摘要：The concept of a stochastic variational inequality has recently been extended to a format that covers, in particular, the optimality conditions for multistage stochastic programming and Nash equilibrium problems. This extension may have great impact on solving stochastic optimization and equilibrium problems in operations research. One of the long-standing methods for solving such optimization problems is the progressive hedging algorithm. That approach is demonstrated here to be applicable also to solving multistage stochastic variational inequality problems under monotonicity. Stochastic complementarity problems are presented as a special case and explored numerically in a linear two-stage formulation.
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