Introduction to Simulation

1. Modeling and simulation

The title "modeling and simulation" designates the complex of activities associated with the construction of models of real world systems and simulating them on a computer. This part gives the reader a short introduction to general simulation and more detailed description of the simulation form called discrete event simulation.

1.1 What is modeling?

Modeling is the process of producing a model. A model is a representation of the construction and working of some system of interest. A model is similar to but simpler than the system it represents. One purpose of a model is to enable the analyst to predict the effect of changes to the system.

First, a model should be a close approximation to the real system and incorporate most of its salient features.

On the other hand, it should not be so complex that it is impossible to understand and experiment with it. A good model is a judicious tradeoff between realism and simplicity.

Simulation practitioners recommend increasing the complexity of a model iteratively. An important issue in modeling is model validity. Model validation techniques include simulating the model under known input conditions and comparing model output with system output.

Generally, a model intended for a simulation study is a mathematical model developed with the help of simulation software.

Mathematical model classifications include deterministic (input and output variables are fixed values) or stochastic (at least one of the input or output variables is probabilistic); static (time is not taken into account) or dynamic (time-varying interactions among variables are taken into account).

1.2 What is simulation?

1.2.1 Definition

Simulation is the process of modeling a proposed or real dynamic system and observing its behavior over time. A simulation study is often set up in order to understand the behavior of a system, or to evaluate the effects of diverse parameters or operating policies. The simulation can be made to anticipate and understand the behavior of everything from a nuclear power station, a chemical reaction to a computer operating system.

Two broad categories of simulations are discrete-event and continuous simulations.

A discrete-event simulation is one where changes in the state of the system occur instantaneously at random points in time as a result of the occurrence of discrete event. For example, in a queuing system where the state of the system is the number of customers in the system (a restaurant for example), the discrete events that change this state are the arrival of a customer