Abstract: In this paper, we consider a generic class of adaptive optimization problems under ... We draw the connections of the APRO model with the stochastic programming and the regular robust ...

With the transformation from the array output power and the magnitude response to linear functions of the autocorrelation sequence of the array weight, the optimization of an adaptive ... a linear ...

for Robust Optimization, including a brief introduction to Stochastic Programming and Chance-Constraint Programming. The notes include two parts. Part 1 is the introduction of some basic theories of ...

In order to better describe the uncertainty of renewable energy output, this paper proposed a novel robust optimization method for new distribution systems based on adaptive data-driven polyhedral ...

This paper presents a study of two-stage adaptive nonlinear robust optimization in dealing with uncertainty in the optimal design and operation of water treatment systems. This work aims to obtain (i) ...