Chapter 13 Simulation

Simulation is a technique usually reserved for studying only the simplest and most straightforward of problems.

True

False

false

A simulation model is designed to arrive at a single specific numerical answer to a given problem.

True

False

false

Simulation typically requires a familiarity with statistics to evaluate the results.

True

False

True

The verification process involves making sure that

the model adequately represents the real-world system.

the model is internally consistent and logical.

the correct random numbers are used.

enough trial runs are simulated.

the model is internally consistent and logical.

The validation process involves making sure that

the model adequately represents the real-world system.

the model is internally consistent and logical.

the correct random numbers are used.

enough trial runs are simulated.

the model adequately represents the real-world system

Which of the following is an advantage of simulation?

It allows time compression.

It is always relatively simple and inexpensive.

The results are usually transferable to other problems.

It will always find the optimal solution to a problem.

It allows time compression.

Which of the following is a disadvantage of simulation?

It is inexpensive even for the most complex problem.

It always generates the optimal solution to a problem.

The results are usually transferable to other problems.

Managers must generate all of the conditions and constraints for solutions they wish to examine.

Managers must generate all of the conditions and constraints for solutions they wish to examine.

A meteorologist was simulating the number of days that rain would occur in a month. The random number interval from 01 to 30 was used to indicate that rain occurred on a particular day, and the interval 31–00 indicated that rain did not occur. What is the probability that rain did occur?

0.30

0.31

1.00

0.70

.30

Simulation is best thought of as a technique to

give concrete numerical answers.

increase understanding of a problem.

provide rapid solutions to relatively simple problems.

provide optimal solutions to complex problems.

increase understanding of a problem.

When simulating the Monte Carlo experiment, the average simulated demand over the long run should approximate the

real demand.

expected demand.

sample demand.

daily demand.

expected demand.

The idea behind simulation is

to imitate a real-world situation.

to study the properties and operating characteristics of a real-world situation.

to draw conclusions and make action decisions based on simulation results.

all of the above.

all of the above

Using simulation for a queuing problem would be appropriate if

the arrival rate follows a Poisson distribution.

the service rate is constant.

the FIFO queue discipline is assumed.

there is a 10% chance an arrival would leave before receiving service.

there is a 10% chance an arrival would leave before receiving service.

A probability distribution has been developed, and the probability of two arrivals in the next hour is 0.20. A random number interval is to be assigned to this. Which of the following would not be an appropriate interval?

01–20

21–40

00–20

00–19

All of the above would be appropriate.

00–20

In a Monte Carlo simulation, a variable that we might want to simulate is

lead time for inventory orders to arrive.

time between machine breakdowns.

time between arrivals at a service facility.

number of employees absent from work each day.

all of the above.

all of the above