We start with basic terminology and concepts of modeling, and decompose the art of modeling as a process. This overview of the process helps clarify when we should or should not use simulation models. We discuss some common missteps made by many inexperienced modelers, and propose a concrete approach for avoiding those mistakes. After a quick review random number and random variate generation, we view the simulation model as a black-box which transforms inputs to outputs. This helps frame the need for designed experiments to help us gain better understanding of the system being modeled. 1 BACKGROUND AND TERMINOLOGY We use models in an attempt to gain understanding and insights about some aspect of the real world. There are many excellent resources available for those who wish to study the topic of modeling in greater depth than we do in this tutorial. See, for example, Law and Kelton (2000), Banks et al. (2005), Weinberg (2001), or Nise (2004). Attempts to model reality assume a prior...
Paul J. Sánchez