AEPS: Efficient SDP Algorithms for Uncertain Optimization

Many engineering applications (wireless telecommunications, roundoff error analysis) require to solve optimization problems involving a certain degree of uncertainty, either deterministic or stochastic. The aim of this project is to handle such problems by developping, analyzing and applying optimization frameworks based on semidefinite programming (SDP) relaxations.

AEPS is a PERSYVAL-Lab Exploratory project. You can find preliminary scientific outcome here.