Sensitivity Analysis without Derivatives
Asen L. Dontchev (University of Michigan)
Abstract: The classical sensitivity analysis developed in the early days of optimization and control revolves around determining derivatives of optimal values and solutions with respect to parameters in the problem considered. In problems with constraints however, (standard) differentiability typically fails. The idea to obtain implicit function theorems without differentiability goes back to Hildebrandt and Graves in their paper from 1927 and has been developed for optimization problems in the 1980s. In this talk some major developments in sensitivity analysis of optimization problems in the last several decades are outlined. Estimates for solution dependence on various perturbations are derived based on regularity properties of mappings involved in the description of the problem. Applications to mathematical programming, numerical optimization and optimal control illustrate the theoretical findings.
optimization and control
Audience: learners
Comments: The address and password of the zoom room of the seminar are sent by e-mail on the mailinglist of the seminar one day before each talk
One World Optimization seminar
Series comments: Description: Online seminar on optimization and related areas
The address and password of the zoom room of the seminar are sent by e-mail on the mailinglist of the seminar one day before each talk
| Organizers: | Sorin-Mihai Grad*, Radu Ioan Boț, Shoham Sabach, Mathias Staudigl |
| *contact for this listing |