时间：9月29日下午1:30
地点：管理学院506
报告题目1：与均衡相关的若干优化问题
报告摘要：均衡是经济学中的重要概念，与均衡相关的各类优化问题也一直受到人们的普遍关注。本报告将介绍几类与均衡相关的最优化问题的研究进展，这些问题主要包括随机变分不等式与随机互补问题、带均衡约束的数学规划问题、广义纳什均衡问题、双层规划问题等。
报告人简介：林贵华教授于2004年博士毕业于日本京都大学，曾任京都大学JSPS外国人特别研究员，现任上海大学管理学院教授、管理科学与工程系主任、运筹优化与决策研究所长。研究兴趣主要是与均衡相关的各种最优化问题及其在管理科学中的应用，在SIAM Journal on Optimization、Mathematical Programming、Mathematics of Computation、European Journal of Operational Research等国际知名期刊上发表学术论文60余篇。主持国家自然科学基金项目4项、省部级项目5项。现任中国运筹学会理事、中国运筹学会数学规划分会理事、上海运筹学会理事、中国双法研究会经济数学与管理数学分会常务理事等，《Pacific Journal of Optimization》（SCI期刊）、《运筹与管理》（管理学部A类期刊）等杂志编委。2007年入选辽宁省百千万人才工程，所指导博士生曾获2014年度辽宁省优秀博士学位论文
报告题目2：The CP-matrix completion problem
摘要： A symmetric matrix $C$ is completely positive (CP) if there exists an entrywise nonnegative matrix $B$ such that $C=BB^T$. The CP-completion problem is to study whether we can assign values to the missing entries of a partial matrix (i.e., a matrix having unknown entries) such that the completed matrix is completely positive. We propose a semidefinite algorithm for solving general CP-completion problems, and study its properties. The algorithm can give a certificate if a partial matrix is not CP-completable, and it almost always gives a CP-completion if it is CP-completable. Computational experiments are also presented to show how CP-completion problems can be solved.
报告人简介：范金燕，上海交通大学数学科学学院教授。2002年在中国科学院数学与系统科学研究院获理学博士学位。主要从事非线性最优化的理论和方法研究，在非线性方程组和完全正优化研究领域取得了一系列重要成果，相关论文发表在Math. Program.、SIAM J. Matrix Anal. Appl.、Math. Comp.等国际期刊上，并出版了专著《非线性方程组数值方法》。现为J. Ind. Manag. Optim.、J. Oper. Res. Soc. China、《计算数学》等学术期刊的编委。2017年荣获“第十三届中国青年女科学家奖”。
报告题目3：Time-Scaling Transformation for Time-Delay Optimal Control Problems
报告摘要：In this talk, we consider a class of nonlinear time-delay optimal control problems with canonical equality and inequality constraints. The control function is approximated by a piecewise constant function, where its heights and switching times are decision variables to be optimized. This approach is known as the control parameterization method. For the variable switching times, the most effective approach is the time scaling transformation, which maps the variable switching times into fixed time points in a new time horizon. However, it is not directly applicable to time-delay optimal control problems, because the fixed time delays, after transformation, become variable time delays. To overcome this difficulty, a new computational approach, which combines the control parameterization technique with a new hybrid time-scaling strategy, is developed for solving this class of time-delay optimal control problems. The varying switching times are transformed, via the new hybrid time-scaling strategy, into fixed switching times, which is much preferred for numerical computation. This new time-scaling strategy is related to two coupled time-delay systems-one defined on the original time scale, in which the switching times are variable, the other defined on the new time scale, in which the switching times are fixed. This is different from the conventional time-scaling transformation widely used in the literature, which is not applicable to systems with time-delays. Numerical results show the effectiveness of the new approach. However, there are two obstacles faced by the new hybrid time scaling transformation: (i) There is no explicit closed form expression for each of the varying time delays; and (ii) the duration for the control vector is required to be greater than or equal to a preset positive value, which is less desirable in actual computation. To overcome these two obstacles, a new novel time-scaling transformation is developed, where an explicit closed form expression for each of the delay times in the new time horizon is given, and the positivity constraint is removed. The control parameterization technique used in conjunction with this novel new timescaling transformation is an effective approach to solving nonlinear optimal control problem with multiple time delays. To demonstrate the effectiveness of the proposed approach, four numerical examples are solved. The results obtained are superior to those obtained by other existing optimal control methods.
报告者简介：余长君 2005 年本科毕业于电子科技大学数学系, 2008 年获得上海大学理学硕士学位, 2012年获得澳大利亚 Curtin University 博士学位。近年来主要从事非线性最优化与最优控制理论、算法及其在信息和工程中的应用的研究. 自 2010 年至今，在
• IEEE Transactions on Automatic Control
• Automatica
• Journal of Global Optimization
• Journal of Optimization Theory and Application
等国际著名学术期刊发表论文三十余篇，其中被 SCI 检索 26 篇， EI 检索 1 篇，参编英
文著作章节 1 部。担任 IEEE TAC, Automatica 等顶级期刊的审稿人。余长君博士的研究工作还得到了同行的广泛关注。根据最新的 Scholar Google 论文引用数据，所发表论文共被引 310 次，单篇最高引用次数 61 次， h-index 为 10， i10-index为 10。 2013 年发表于 Optimization Letters 的论文:An exact penalty function method for nonlinear mixed discrete programming problems 入选 2014 年 ESI 高被引论文。主持国家自然科学基金青年基金 1 项, 面上项目 1 项, 参与国家自然科学重点/面上基金 4 项, 做为 Research Fellow 参与澳大利亚国家科研委员会 Discovery 基金 1项. 2016 年 7 月受邀担任于蒙古乌兰巴托举行的第十届 International Conference on Optimization: Techniques and Applications (ICOTA) 大会秘书。 2017 年 10 月，受邀参加首届中国运筹青年论坛，做张贴报告。
受邀担任
• Journal of Industrial Management and Optimization
• Pacific Journal of Optimization
• Dynamics of Continuous, Discrete and Impulsive Systems, Series B
等最优化与最优控制领域内知名 SCI 期刊的客座编委 (Guest Editor)。2015 年入选首批上海市青年东方学者， 2016 年 12 月当选上海市运筹学会第四届理事会常务理事、秘书长。
报告题目4：Convergence analysis of sample average approximation of two-stage stochastic generalized equations
摘要：A solution of two-stage stochastic generalized equations is a pair: a first stage solution which is independent of realization of the random data and a second stage solution which is a function of random variables. This paper studies convergence of the sample average approximation of two-stage stochastic nonlinear generalized equations. In particular, an exponential rate of the convergence is shown by using the perturbed partial linearization of functions. Moreover, sufficient conditions for the existence, uniqueness, continuity, and regularity of solutions of two-stage stochastic generalized equations are presented under an assumption of monotonicity of the involved functions. These theoretical results are given without assuming relatively complete recourse and are illustrated by two-stage stochastic non-cooperative games of two players.
报告者简介：孙海琳现为南京理工大学经济管理学院副教授，2013年8月于哈尔滨工业大学获得博士学位，在博士期间为英国南安普顿大学和香港理工大学的联合培养博士研究生。2007年7月于吉林大学获得学士学位。其主要研究方向是运筹学、随机优化、风险测度、投资组合。目前已在《Mathematical Programming Series A》、《SIAM Journal on Optimization》、《Journal of Mathematical Analysis and Applications》等国内外重要学术期刊上发表多篇论文，并主持国家自然科学基金面上项目、青年基金和江苏省自然科学基金青年基金各1项。
