Digital twinning presents an exciting opportunity enabling real-time optimization of the
control and operations of cyber-physical systems (CPS) with data-driven simulations, while …

This paper is concerned with the efficient estimation of the risk measure of a system where
the estimation requires solving a two-stage simulation optimization problem. The first stage …

Ordinal optimization (OO) is a widely-studied technique for optimizing discrete-event
dynamic systems (DEDS). It evaluates the performance of the system designs in a finite set …

Digital twin technology is increasingly ubiquitous in manufacturing and there is a need to
increase the efficiency of optimization methods that use digital twins to answer questions …

Many decision problems in modern industries involve the performance optimization of
discrete-event dynamic systems. Because of the stochasticity of these systems, performance …

In many real-world problems, we are faced with the problem of selecting the best among a
finite number of alternatives, where the best alternative is determined based on context …

We consider the simulation optimization problem of selecting the best system design from a
finite set of alternatives, which is known as ranking and selection (R&S). Many fully …

Stochastic simulation is typically deployed for offline system design and control; however,
the time delay in executing simulation hinders its application in making online decisions …

We consider how to allocate simulation budget to estimate the risk measure of a system in a
two-stage simulation optimization problem. In this problem, the first stage simulation …

Simulation optimization has found great success in automation science and engineering,
such as the optimization of manufacturing systems, thanks to its capability to fully account for …