This document provides a brief proposal for “Robust Optimization & Robust Control Synthesis” reading group.

Portfolio Optimization is based on the efficient allocation of several assets, which can get heavily affected by uncertainty in input parameters. So we must look for such solutions give us steady results uncertain conditions too. Recently, optimization problems are being dealt with robust approach. With this development, interest researchers has been shifted toward portfolio optimization. In pa...

Hub location-allocation problems are currently a subject of keen interest in the research community. However, when this issue is considered in practice, significant difficulties such as traffic, commodity transportation and telecommunication tend to be overlooked. In this paper, a novel robust mathematical model for a p-hub covering problem, which tackles the intrinsic uncertainty of some param...

We study statistical inference and distributionally robust solution methods for stochastic optimization problems, focusing on confidence intervals optimal values solutions that achieve exact coverage asymptotically. develop a generalized empirical likelihood framework—based distributional uncertainty sets constructed from nonparametric f-divergence balls—for Hadamard differentiable functionals,...