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报告承办单位: 数学与统计学院

报告题目: An efficient Newton-type algorithm for a novel kind of tensor complementarity problems

报告内容: We introduce a novel kind of structured tensor based on the concept of $P_0$ mapping, and the solvability of the corresponding tensor complementarity problem is discussed. We show that the solution set is nonempty and compact if the related tensor is an $R_0$-tensor. Especially, we also introduce a new structured tensor related to the $P$ mapping on $R^n_+$ and prove that the corresponding tensor complementarity problem has a unique solution. Based on the structure of the newly introduced tensor, we propose a smoothing Newton-type algorithm with a new one-dimensional line search rule for solving the corresponding tensor complementarity problem.

报告人姓名:  张立平

报告人所在单位: 清华大学

报告人职称/职务及学术头衔:  副教授、博士导师

报告时间:  2020年9月24日（星期四）：19:30-20:30

报告方式:  线上腾讯会议，会议号ID：426-463-938

报告人简介:  张立平，清华大学长聘副教授，博士生导师，研究方向最优化理论算法及应用，在求解互补与变分不等式问题、半无限规划、张量优化等方面取得了一些有意义的结果。已发表高质量论文三十余篇、连续获得多项国家自然科学基金资助。曾获得教育部自然科学奖二等奖和北京市科学技术奖二等奖。