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Chapter 14
Simulation
2
What Is Simulation?
 Simulation: A model of a complex system and the
experimental manipulation of the model to observe
the results.
Systems that are best suited to being simulated are
dynamic, interactive, and complicated.
 Model: An abstraction of a real system.
It is a representation of the objects within the system and
the rules that govern the interactions of the objects.
3
Constructing Models
 Continuous simulation
 Treats time as continuous and expresses changes
in terms of a set of differential equations that
reflect the relationships among the set of
characteristics.
 Meteorological models fall into this category.
4
Constructing Models
 Discrete event simulation
 consists of entities, attributes, and events.
 Entity: the representation of some object in the
real system that must be explicitly defined
 Attribute: some characteristic of a particular
entity
 Event: an interaction between entities
5
Queuing Systems
 Queuing system: a discrete-event model that
uses random numbers to represent the arrival
and duration of events.
 The system is made up of servers and queues of
objects to be served.
 The objective is to utilize the servers as fully as
possible while keeping the wait time within a
reasonable limit.
6
Queuing Systems
 To construct a queuing model, we must know the following
four things:
 the number of servers
 the number of events and how they affect the system
 in order to determine the rules of entity interaction
 the distribution of arrival times
 in order to determine if an entity enters the system
 the expected service time
 in order to determine the duration of an event
7
Meteorological Models
 Meteorological models are based on the time-
dependent, partial differential equations of
fluid mechanics and thermodynamics.
 Initial values for the variables are entered
from observation, and the equations are
solved to define the values of the variables at
some later time.
8
Meteorological Models
 Computer models are designed to aid the
weathercaster, not replace him or her.
 The outputs from the computer models are
predictions of the values of variables in the
future.
 It is up to the weathercaster to determine what the
values mean.
9
Hurricane Tracking
 The modules for hurricane tracking are called
relocatable models, because they are applied to a
moving target.
 The Geophysical and Fluid Dynamics Laboratory
(GFDL) developed the most recent hurricane model
in order to improve the prediction of where a
hurricane would make landfall.
10
Hurricane Tracking
Figure 14.2
Improvements in
hurricane models
11
Discrete or Continuous?
Consider the Pepper Moth Population Simulation
in Lab 7.
Is it an example of discrete or continuous
simulation?

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Simulation.ppt

  • 2. 2 What Is Simulation?  Simulation: A model of a complex system and the experimental manipulation of the model to observe the results. Systems that are best suited to being simulated are dynamic, interactive, and complicated.  Model: An abstraction of a real system. It is a representation of the objects within the system and the rules that govern the interactions of the objects.
  • 3. 3 Constructing Models  Continuous simulation  Treats time as continuous and expresses changes in terms of a set of differential equations that reflect the relationships among the set of characteristics.  Meteorological models fall into this category.
  • 4. 4 Constructing Models  Discrete event simulation  consists of entities, attributes, and events.  Entity: the representation of some object in the real system that must be explicitly defined  Attribute: some characteristic of a particular entity  Event: an interaction between entities
  • 5. 5 Queuing Systems  Queuing system: a discrete-event model that uses random numbers to represent the arrival and duration of events.  The system is made up of servers and queues of objects to be served.  The objective is to utilize the servers as fully as possible while keeping the wait time within a reasonable limit.
  • 6. 6 Queuing Systems  To construct a queuing model, we must know the following four things:  the number of servers  the number of events and how they affect the system  in order to determine the rules of entity interaction  the distribution of arrival times  in order to determine if an entity enters the system  the expected service time  in order to determine the duration of an event
  • 7. 7 Meteorological Models  Meteorological models are based on the time- dependent, partial differential equations of fluid mechanics and thermodynamics.  Initial values for the variables are entered from observation, and the equations are solved to define the values of the variables at some later time.
  • 8. 8 Meteorological Models  Computer models are designed to aid the weathercaster, not replace him or her.  The outputs from the computer models are predictions of the values of variables in the future.  It is up to the weathercaster to determine what the values mean.
  • 9. 9 Hurricane Tracking  The modules for hurricane tracking are called relocatable models, because they are applied to a moving target.  The Geophysical and Fluid Dynamics Laboratory (GFDL) developed the most recent hurricane model in order to improve the prediction of where a hurricane would make landfall.
  • 11. 11 Discrete or Continuous? Consider the Pepper Moth Population Simulation in Lab 7. Is it an example of discrete or continuous simulation?