Scientists have developed a new optimization approach that combines both day-ahead optimization and real-time optimization to improve operations of PV-driven EV charging stations. The framework is ...

Stochastic programming can effectively describe many decision-making problems in uncertain environments. Unfortunately, such programs are often computationally demanding to solve. In addition, their ...

Course in stochastic optimization with an emphasis on formulating, solving, and approximating optimization models under uncertainty. Topics include: Models and applications: extensions of the linear ...

We study the asymptotic behavior of the statistical estimators that maximize a not necessarily differentiable criterion function, possibly subject to side constraints (equalities and inequalities).

This is where Process Optimization with Simulation emerges as a critical tool, offering a powerful way to model, analyze, and ...