题目：Regaining tractability in some large scale/uncertain engineering optimization problems
报告人：Aharon Ben-Tal（Technion – Israel Institute of Technology）
摘要: The need to solve real-life optimization problems poses frequently a severe challenge, as the underlying mathematical programs threatens to be intractable. The intractability can be attributed to any of the following properties: large dimensionality of the design dimension; lack of convexity; parameters affected by uncertainty. In problems of designing optimal mechanical structures, the mathematical programs typically have hundreds of thousands of variables, a fact which rules out the use of advanced modern solution methods, such as Interior Point method. Some Signal Processing and Estimation problems may result in nonconvex formulations. In the wide area of optimization under uncertainty classical approaches, such as chance (probabilistic) constraints, give rise to nonconvex NP-hard problems. Nonconvexity also occurs in some Robust Control problems.
报告人简介：Aharon Ben-Tal is a Professor of Operations Research and Optimization at the Faculty of Industrial Engineering and Management at the Technion – Israel Institute of Technology. Recently the focus of his research is on optimization problems affected by uncertainty. In the last 15 years, he has devoted much effort to engineering applications of optimization methodology and computational schemes. He has published more than 120 papers in professional journals and co-authored three books: Optimality in Nonlinear Programming: A Feasible Direction Approach (Wiley-Interscience, 1981), Lectures on Modern Convex Optimization: Analysis, Algorithms and Engineering Applications (SIAM-MPS series on optimization, 2001) and Robust Optimization (Princeton University press, 2009). He was awarded in 2007 the EURO Gold Medal and was named INFORMS Fellow in 2010.