group_ch15_1.doc Page 1 of 1 Name: _______________________
15.1
Simulation is a rarely used quantitative analysis tool.
ANSWER:
15.3
While simulations can be completed by manual computations, effective
simulations generally use a computer to simulate many thousands of events.
ANSWER:
15.5
A major advantage of using simulation techniques is to be able to study
the interactive effect of individual components/variables.
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15.7
Any randomly selected integer used to start the Von Neumann midsquare
method of random number generation generates a stream of random numbers.
ANSWER:
15.9
When using a random number generator, one should never start in the
middle of the table of random numbers.
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15.11
Simulation models are used quite often to investigate a system’s
response to deterministic elements of the system.
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15.13
Simulation is a valuable technique for analyzing various maintenance
policies before actually implementing
them.
ANSWER:
15.15
The primary purpose of simulation is to generate numbers describing the
state of a real system.
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15.17
A simulation may take on a logical or mathematical form as well as a
physical form.
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15.19
When faced with a queuing or waiting line problem, it is typically
preferable to utilize an analytical model rather than a simulation model, since
the analytical model provides a greater amount of information.
ANSWER:
15.21
If we wish to use a Monte Carlo simulation model, we must run the model a
number of times and look at the collection of answers generated.
ANSWER:
15.23
Analytical models are preferable to simulation models in that the
analytical model gives more precise results.
ANSWER:
15.25
Simulation models may contain both deterministic and probabilistic
variables.
ANSWER:
15.27
If we are using a Monte Carlo simulation model, we should expect the
model to produce the same results for each set of random numbers used.
ANSWER:
15.29
The first step in constructing a simulation is constructing the numerical
model.
ANSWER:
15.31
Monte Carlo simulation requires that we run the simulation dozens of
times with the same set of random numbers to see how the solutions differ as a
function of the random numbers used.
ANSWER:
15.33
If, for a simple queuing or waiting line problem, we compare the solution
from an analytical model with that from a simulation, we will typically find
them to be exactly the same.
ANSWER:
15.35
One of the limitations of analytical models is that they typically
consider the system only in steady state or "on average."
ANSWER:
15.37
Most simulations are done to identify minimum cost alternatives.
ANSWER:
15.39
When we decide to perform a simulation, it really does not matter which
simulation language we use.
ANSWER:
15.41
One of the advantages to simulation is that it will usually give us very
precise answers to extremely complex problems.
ANSWER:
15.43
The wider the variation among results produced by using different sets of
random numbers, the longer we need to run the simulation to obtain reliable
results.
ANSWER:
15.31
Monte Carlo simulation requires that we run the simulation dozens of
times with the same set of random numbers to see how the solutions differ as a
function of the random numbers used.
ANSWER:
15.33
If, for a simple queuing or waiting line problem, we compare the solution
from an analytical model with that from a simulation, we will typically find
them to be exactly the same.
ANSWER:
15.35
One of the limitations of analytical models is that they typically
consider the system only in steady state or "on average."
ANSWER:
15.37
Most simulations are done to identify minimum cost alternatives.
ANSWER:
15.39
When we decide to perform a simulation, it really does not matter which
simulation language we use.
ANSWER:
15.41
One of the advantages to simulation is that it will usually give us very
precise answers to extremely complex problems.
ANSWER:
15.43
The wider the variation among results produced by using different sets of
random numbers, the longer we need to run the simulation to obtain reliable
results.
ANSWER: