Dynamic System Simulation for Decision Support

Dynamic System Simulation for Decision Support

Norman Pendegraft (University of Idaho, USA) and Mark Rounds (University of Idaho, USA)
DOI: 10.4018/978-1-59904-843-7.ch035
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Abstract

Simulation is a powerful methodology for decision support because it allows managers to experiment with models prior to implementing a policy or decision. There are several approaches to computer simulation: continuous event simulation, discrete event simulation, and Monte Carlo simulation. Continuous event simulation can be used to model dynamic system which cannot otherwise be easily modeled.

Key Terms in this Chapter

Flow: An object in a dynamic systems simulation that represents changes in stocks.

Stock: An object in a dynamic systems simulation that represents some aspect of the state of system which may change over time.

Discrete Event Simulation: A simulation methodology in which events cause the state of the system to change at specific points in time.

Continuous Simulation: A simulation methodology in which uses the state of the system changes continuously in time.

Monte Carlo Simulation: A simulation in which random events are modeled using pseudo random number generators so that many replications of the random events may be evaluated statistically.

Simulation: Experimenting with a model (typically a computer model) of a system.

System Dynamics: A modeling approach developed by Forrester (1961) that models complex systems. An engineering discipline that deals with the mathematical analysis of dynamic systems.

Dynamic System: A system which has a state vector that changes over time.

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