Solving monotone stochastic variational inequalities and complementarity problems by progressive hed

报告题目:Solving monotone stochastic variational inequalities and complementarity problems by progressive hed

报 告 人:Prof. Sun Jie

报告时间:2019/4/10 11:00:00

报告地点:学院205室


专家简介:Sun Jie,现任新加坡国立大学讲座教授, 澳大利亚科廷大学杰出研究教授。孙捷教授曾获新加坡国立大学杰出大学研究者奖,也是国大唯一获得讲座教授职务的中国移民,是国际信息科学学院评出的 2002-2012期间被引用率最高的学者之一。孙捷教授任新加坡- 麻省理工 学院联盟院士,曾任麻省理工学院和瑞士联邦工业学院的访问科学家等职。孙捷教授的研究领域主要聚焦于 金融工程 与风险管理、 投资 决策 、运筹与优化、 运筹与管理 等领域,他在 Operations Research, Mathematical Programming, Mathematics of Operations Research and SIAM Journal on Optimization, Management Science,Math. Finance等国际运筹与管理、优化与金融决策领域顶级期刊及国际著名期刊发表论文150余篇,其论文被各个领域他引次数超过3000次。孙教授目前是亚太地区优化与运筹协会主席,并担任国际多个优化与运筹管理领域著名期刊的主编和副主编。


报告摘要:The concept of a stochastic variational inequality has recently been articulated in a new way that is able to cover, in particular, the optimality conditions for a multistage stochastic programming problem. One of the long-standing methods for solving such an optimization problem under convexity is the progressive hedging algorithm. That approach is demonstrated here to be applicable also to solving multistage stochastic variational inequality problems under monotonicity, thus increasing the

range of applications for progressive hedging. Stochastic complementarity problems as a special case are explored numerically in a linear two-stage formulation.