Discrete-Event Simulation:A First Course
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07-10-2010, 10:52 AM

This article is presented by:
Steve Park and Larry Leemis
College of William and Mary
Discrete-Event Simulation:A First Course
Technical Attractions of Simulation

Ability to compress time, expand time
Ability to control sources of variation
Avoids errors in measurement
Ability to stop and review
Ability to restore system state
Facilitates replication
Modeler can control level of detail

What is discrete-event simulation?
Modeling, simulating, and analyzing systems
Computational and mathematical techniques
Model: construct a conceptual framework that describes a system
Simulate: perform experiments using computer implementation of the model
Analyze: draw conclusions from output that assist in decision making process
We will first focus on the model

Characterizing a Model

Deterministic or Stochastic
Does the model contain stochastic components?
Randomness is easy to add to a DES
Static or Dynamic
Is time a significant variable?
Continuous or Discrete
Does the system state evolve continuously or only at discrete points in time?
Continuous: classical mechanics
Discrete: queuing, inventory, machine shop models
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