Abstract: Factor screening searches for the really important inputs (factors) among the many inputs that are changed in a realistic simulation experiment. Sequential bifurcation (SB) is a sequential method that changes groups of inputs simultaneously. SB is the most efficient and effective...

This article illustrates simulation optimization through an (s, S) inventory management system.In this system, the goal function to be minimized is the expected value of specific inventory costs.Moreover, specific constraints must be satisfied for some random simulation responses, namely the...

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...

Classic linear regression models and their concomitant statistical designs assume a univariate response and white noise.By definition, white noise is normally, independently, and identically distributed with zero mean.This survey tries to answer the following questions: (i) How realistic are...

This paper proves that it is wrong to require that regressing a model's outputs on the observed real outcomes gives a 45 degrees line through the origin (unit slope, zero intercept).Therefore this paper proposes an alternative requirement: the responses of the model and the real system should...

This article reviews so-called screening in simulation; i.e., it examines the search for the really important factors in experiments with simulation models that have very many factors (or inputs). The article focuses on a most efficient and effec- tive screening method, namely Sequential...

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...