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Modeling methodologies
• Ascaledrepresentationofaphysicalobject,suchasa1:18diecastmodelofaFerrari,aclay model of a proposed packaging bottle, or a scale model of the solar system.
• Agraphicalorsymbolicvisualization,suchasaflowchartofofficeprocedures,theboard game Monopoly (which represents the hotels and facilities of Atlantic City), or an architect’s plans for a building.
• An analytical or mathematical formula that yields a static, quantitative solution. For instance, an analytic model might consist of several independent sample observations that have been transformed according to the rules of the model. Common examples of analytic models are spreadsheet models or linear programming models.
• Amathematicaldescriptionthatincorporatesdataandassumptionstologicallydescribethe behavior of a system. This type of model is typically dynamic—it has a time component and shows how the system evolves over time. ExtendSim products are tools for building mathe- matically-based, dynamic models of systems.
Dynamic modeling is the foundation for computer modeling. Thus, for purposes of this man- ual, the word “model” will be used to mean a description of the dynamic behavior of a system or process.
ExtendSim models typically have a time component and can show cause and effect and the flow of entities throughout a system (you can also create ExtendSim animations that show spa- tial relationships.)
Simulation
The Merriam-Webster OnLine Dictionary defines simulation as “the imitative representation of the functioning of one system or process by the functioning of another.” This means that to determine how an actual system functions, you would build a model of the system and see how the model functions.
Simulations run in simulation time, an abstraction of real time. As the simulation clock advances, the model determines if there have been changes, recalculates its values, and outputs the results. If the model is valid, the outputs of the simulation will be reflective of the perfor- mance or behavior of the real system.
Simulation with ExtendSim means that instead of interacting with a real system you create a logical model that corresponds to the real system in certain aspects. You simulate the opera- tions or dynamics of the system, then analyze one or more areas of interest. You do this in order to reduce risk and uncertainty so that you can make informed, timely decisions.
Modeling methodologies
The formalism you use to specify a system is termed a modeling methodology. The three main modeling methodologies are:
• Continuous
• Discrete event
• Discrete rate
These methodologies are described, compared, and contrasted in the later topics in this chapter.
In addition to the main modeling methodologies listed above, other modeling approaches are useful and will be discussed in this chapter. These approaches are usually based on one of the three main methods and include:
Tutorial

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