Selected topics in robust convex optimization

• 成果类型: Article; Proceedings Paper
• 署名作者: Ben-Tal, Aharon; Nemirovski, Arkadi
• 署名单位: University System of Georgia; Georgia Institute of Technology; Technion Israel Institute of Technology
• 刊物名称: MATHEMATICAL PROGRAMMING
• ISSN/ISSBN: 0025-5610
• DOI: 10.1007/s10107-006-0092-2
• 发表日期: 2008
• 页码: 125-158
• 关键词: squared error estimation; tractable approximations; systems; noise; MODEL

摘要

Robust Optimization is a rapidly developing methodology for handling optimization problems affected by non-stochastic uncertain-but- bounded data perturbations. In this paper, we overview several selected topics in this popular area, specifically, (1) recent extensions of the basic concept of robust counterpart of an optimization problem with uncertain data, (2) tractability of robust counterparts, (3) links between RO and traditional chance constrained settings of problems with stochastic data, and (4) a novel generic application of the RO methodology in Robust Linear Control.