应航天航空学院机械结构强度与振动国家重点实验室邀请，墨西哥科学院院士、墨西哥CINVESTVA-IPN国家研究院计算机科学学院教授Oliver Scheutze博士将来我校进行学术交流访问, 并就他在多目标最优化问题 最新研究进展做学术报告，同时开展学术交流。具体安排如下：

学术报告和交流：

题目：Continuation Methods for the Numerical Treatment of Multi- and Many Objective Optimization Problem

报告时间：  2019年10月25日（星期五）上午8：30- 10：00

交流时间：上午10：00- 11：00

地点: 航天学院 第四会议室

Abstract:

In many applications the problem arises that several objectives have to be optimized concurrently leading to multi-objective optimization problems (MOPs). As a general example, two common goals in product design are certainly to maximize the quality of the product and to minimize its cost. Since these two goals are typically contradicting, it comes as no surprise that the solution set -- the so-called Pareto set -- of a MOP does in general not consist of one single solution but rather of an entire set of solutions. More precisely, the Pareto set of a continuous MOP typically forms at least locally a (k-1)-dimensional manifold, where k is the number of objectives involved in the problem.

In this talk, we will address continuation methods that make use of this geometric property of the Pareto set. Given an initial solution of a MOP, continuation methods perform a movement along the solution set and are thus the most effective local solvers for such problems. First, we will address the treatment of problems with few objectives (say, k from 2 to 4), and will afterwards propose possible strategies to cope with so-called many objective optimization problems (i.e., MOPs where k is larger than 4). The applicability and usefulness of all methods will be demonstrated on benchmark problems as well as on two applications from industrial laundry design and injection molding.

Oliver Scheutze博士简历：

Oliver Scheutze博士是墨西哥科学院院士、墨西哥CINVESTVA-IPN国家研究院计算机科学学院教授，博士生导师，同时客座墨西哥Cuajimalpa大学计算机学院Titula C级教授（该校教授序列最高等级）。Scheutze博士2004博士毕业于德国Paderborn大学计算机与数学系。2005年加入墨西哥CINVESTVA-IPN国家研究院，历任访学教授、助理教授、副教授和教授。国际期刊Mathematical and Computational Applications的主编(Editor-in-Chief)。国际期刊Computational Optimization and Applications、Mathematical Problems in Engineering、International Journal of Metaheuristic 的编辑(Editor)。Oliver Scheutze博士的主要研究方向为演化式多目标优化的数值算法、非线性方程解算方法、非线性动力学沿拓方法、随机搜索方法、基于集合的离散算法等。从教以来，Scheutze博士共撰写学术专著1部、教科书3部，参与编写10部著作的相关章节，发表期刊和会议论文140余篇。截止2019年6月，其研究成果已达到2500次引用，H-index为26，i10-index为60。Scheutze博士共主持和参研14个科研项目，资助国家包括墨西哥、美国、英国、德国、法国等。