I start this contribution with an overview of my personal involvement—as an Operations Research consultant—in several engineering case-studies that may raise ethical questions; these case studies employ simulation models. Next, I present an overview of the recent literature on ethical issues...

Design Of Experiments (DOE) is needed for experiments with real-life systems, and with either deterministic or random simulation models. This contribution discusses the different types of DOE for these three domains, but focusses on random simulation. DOE may have two goals: sensitivity analysis...

Sensitivity analysis may serve validation, optimization, and risk analysis of simulation models.This review surveys classic and modern designs for experiments with simulation models.Classic designs were developed for real, non-simulated systems in agriculture, engineering, etc.These designs...

This contribution discusses experiments with many factors: the case study includes a simulation model with 92 factors.The experiments are guided by sequential bifurcation.This method is most efficient and effective if the true input/output behavior of the simulation model can be approximated...

Whereas Operations Research has always paid much attention to optimization, practitioners judge the robustness of the 'optimum' solution to be of greater importance.Therefore this paper proposes a practical methodology that is a stagewise combination of the following four proven techniques: (1)...

This paper provides a survey of simulation in supply chain management.It reviews four types of simulation, namely spreadsheet simulation, system dynamics, discreteevent simulation, and business games.Which simulation type should be applied, depends on the type of managerial question to be...

The bootstrap is a simple but versatile technique for the statistical analysis of random simulations.This tutorial explains the basics of that technique, and applies it to the well-known M/M/1 queuing simulation.In that numerical example, different responses are studied.For some responses,...

Abstract: This article surveys optimization of simulated systems. The simulation may be either deterministic or random. The survey reflects the author’s extensive experience with simulation-optimization through Kriging (or Gaussian process) metamodels. The analysis of these metamodels may use...