A model is a representation of a system for the purpose of studying the system.

A simulation model is a particular type of mathematical model (one that uses symbolic notation and mathematical equations to represent a system) of a system.

There are four phases to modeling & simulation:

• Period of Discovery or Orientation (1 & 2)
• Model Building and Data Collection (3, 4, 5, 6, & 7)
• Running the Model (8, 9, & 10)
• Implementation (11 & 12)

These can be broken down into the following twelve parts:

1. Problem Formation
2. Setting of Objective and Overall Design
3. Model Building - queuing models, Markov, etc.
4. Data Collection - statistical models (distributions), histograms, bivariate data (regression)
5. Coding
6. Verification - Turing test
7. Validation - steady state, hypothesis testing
8. Experimental Design - steady state, hypothesis testing
9. Production Runs and Analysis - steady state, hypothesis testing
10. Additional Runs
11. Document Program and Report Results
12. Implementation

The flow chart for this is Figure 1.3, from Banks, et. al.