The goal is to implement, analyze, and compare various stochastic control techniques—from classical methods to modern machine learning approaches—with applications to real-world problems in portfolio ...

Note that the higher the dimensionality (parameters number) of the optimization problem, the harder it is, and the slower the optimization process is. A family of problem-independent, gradient-free, ...

A global research team led by scientists from China’s Tianjin Renai College has developed a novel stochastic optimization technique for enhanced dispatching and operational efficiency in PV-powered ...

Abstract: We consider a nonlinear discrete stochastic control system, and our goal is to design afeedback control policy in order to lead the system to a prespecified state. We adopt a Stochastic ...

Abstract: In this paper, we study discrete-time feedback optimization in stochastic scenarios. Specifically, we consider a discrete-time stochastic nonlinear system where the goal is to optimize its ...