Foundations of Simulation Modeling

AbstractSimulation modeling is an important step of a simulation study. It concerns with the creation of an efficient simulation model as accurate as needed to mimic the behavior of the underlying system and to reproduce useful observations for subsequent analysis. This introductory article discusses three main simulation modeling methods: discrete‐event simulation, continuous simulation, and agent‐based simulation. In particular, three discrete‐event simulation modeling paradigms are introduced: event scheduling, process interaction, and activity scanning. Several modeling issues are exemplified by a simple single‐server queueing system and a slightly more complex multiple‐server finite capacity queueing system with impatient customers. Continuous simulation is briefly discussed to draw the differences between discrete‐event and continuous simulations. Simulating emergent behavior as a common purpose of agent‐based simulation is demonstrated by a classic game of life model and a variation model. Monte‐Carlo simulation and other simulation modeling formalisms are briefly highlighted.