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Introduction to Simulation
Learning Objectives
•
Understand what simulation is and how it aids in the analysis
of a problem.
•
Learn why simulation is a significant problem
‐
solving tool.
•
Understand the difference between static and dynamic
simulation.
•
Identify the important role probability distributions, random
numbers, and the computer play in implementing simulation
models.
•
Realize the relative advantages and disadvantages of
simulation models.
•
Given a probability distribution simulate a sequence of
random variables from that probability distribution
What is a Simulation?
A simulation develops a numerical model
whose behavior resembles that of a real
system over some specified time interval
•
Continuous simulation systems
‐
system changes its
state continuously over time.
•
Deterministic – often require differential equations
•
Stochastic/random – uses random numbers
•
Hybrid
•
Discrete simulation systems
‐
system changes its
state at discrete points in time
Simulation Analysis
•
Understand what simulation is and how it aids in the
analysis of a problem.
•
Understand why simulation is a significant problem
solving tool.
•
Understand the difference between static and dynamic
simulation.
•
Identify the important role probability distributions,
random numbers, and the computer play in implementing
simulation models.
•
Realize the relative advantages and disadvantages of
simulation models.
•
Given a probability distribution simulate a sequence of
random variables from that probability distribution
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Applications of Simulation
•
New product development
•
Airline overbooking
•
Queuing systems
•
Inventory policy
•
Traffic flow in intelligent transportation systems
Advantages of Simulation
•
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 Spring '10
 J.LOUTEN
 Probability distribution, Cumulative distribution function, Discrete probability distribution, random numbers

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