Mathematical Sciences: Eigenvalue Optimization and Robust Mathematical Programming

本项目将研究特征值优化和鲁棒性 非线性规划的方法 特征值的研究 优化将考虑光谱的变分性质， 的最大真实的部分的映射 江西篇章 鲁棒全局算法与鲁棒局部理论 使用凸复合函数的行为将是 开发 将特别注意的技术， 允许放松规律性假设。 该研究在复杂化学模型中具有应用价值 过程，结构优化设计，反馈稳定， 和动力系统的稳定性。

This project will study eigenvalue optimization and robust methods in nonlinear programming. The research on eigenvalue optimization will consider variational properties of the spectral radius map and the mapping that yields the maximum real part of the spectrum. Robust global algorithms and robust local theory using the behavior of convex composite functions will be developed. Particular attention will be given to techniques that permit the relaxation of regularity hypotheses. This research has applications in modeling complex chemical processes, optimal design of structures, feedback stabilization, and stabilization of dynamical systems.