Simulation Model F Exam with 100%
Complete Solutions
Explain how Monte Carlo simulation uses random numbers. - Answer- Correct First, a
cumulative probability distribution is set up for the element being modeled. From this, a
set of random number intervals is established. A random number is generated and
matched against the set of intervals. The random number will fall into only one interval,
and that determines the value for the element being modeled.
Explain the difference between random numbers and random number intervals. -
Answer- Correct Random numbers are a series of digits that have been selected by a
totally random process. Random number intervals are numbers used to represent each
possible value or outcome in a computer simulation. During simulation, a particular
random number is matched against the random number intervals to determine the value
for the element being modeled that particular time.
Explain what is meant by the concept of "time compression" in simulation modeling. -
Answer- Correct The effects of OM policies over many months or years can be obtained
by computer simulation in a short time.
Explain what is meant by the statement: "simulation is not limited to using the standard
probability distributions." - Answer- Correct "Standard models" include normal, binomial,
beta, uniform, Poisson, exponential, and other probability distributions. Each has a
specific set of assumptions and parameters. Real-world (empirical) systems can have
any distribution imaginable. Simulation can mimic these real-world distributions by the
use of random number intervals based on real-world behavior, and can therefore
generate more realistic models than would occur if a standard model were used in place
of a system-specific one.
From a portion of a probability distribution, you read that P(demand = 0) is 0.05 and
P(demand = 1) is 0.10. The cumulative probability for demand = 1 would be which of the
following? - Answer- .15
From a portion of a probability distribution, you read that P(demand = 0) is 0.05,
P(demand = 1) is 0.10, and P(demand = 2) is 0.20. What are the two-digit random
number intervals for this distribution beginning with 01? - Answer- Correct 01 through
05, 06 through 15, and 16 through 35
From a portion of a probability distribution, you read that P(demand = 0) is 0.25, and
P(demand = 1) is 0.30. What are the random number intervals for this distribution
beginning with 01? - Answer- Correct 01 through 25, and 26 through 55
, From a portion of a probability distribution, you read that P(demand = 1) is 0.05,
P(demand = 2) is 0.15, and P(demand = 3) is .20. The cumulative probability for
demand = 3 would be which of the following? - Answer- Correct Cannot be determined
from the information given.
Historical records on a certain product indicate the following behavior for demand. The
data represent the 288 days that the business was open during 2000. Convert these
data into random number intervals. (Round each probability used to 2 decimal places,
e.g., 0.36.)
demand in cases: 7,8,9,10,11,12
number of occuranc: 52,9,14,39,72,102 - Answer- demand in cases: 7,8,9,10,11,12
number of occuranc: 52,9,14,39,72,102
probablility: .18, .03, .05. .14, .25, .35
cumulative probab:
.18, .21, .26, .40, .65, 1.0
random number intercals:
01-18, 19-21, 22-26, 41-65, 66,00
Identify five applications of simulation. - Answer- Correct The five applications of
simulation can be picked from a list in Table F.1. Some examples are: traffic-light timing,
bus scheduling, plant layout, production scheduling, inventory planning, and assembly-
line balancing.
Identify the seven steps involved in using simulation. - Answer- 1. Define the problem.
2. Introduce the important variables associated with the problem.
3. Construct a numerical model.
4. Set up possible courses of action for testing by specifying values of variables.
5. Run the experiment.
6. Consider the results (possibly modifying the model or changing data inputs).
7. Decide what course of action to take.
Identify, in order, the five steps required to implement the Monte Carlo simulation
technique. - Answer- Correct (1) Setting up a probability distribution for important
variables. (2) Building a cumulative probability distribution for each variable. (3)
Establishing an interval of random numbers for each variable. (4) Generating random
numbers. (5) Actually simulating a series of trials.
"Time compression" and the ability to pose "what-if?" questions are elements of: -
Answer- Correct the advantages of simulation.
Complete Solutions
Explain how Monte Carlo simulation uses random numbers. - Answer- Correct First, a
cumulative probability distribution is set up for the element being modeled. From this, a
set of random number intervals is established. A random number is generated and
matched against the set of intervals. The random number will fall into only one interval,
and that determines the value for the element being modeled.
Explain the difference between random numbers and random number intervals. -
Answer- Correct Random numbers are a series of digits that have been selected by a
totally random process. Random number intervals are numbers used to represent each
possible value or outcome in a computer simulation. During simulation, a particular
random number is matched against the random number intervals to determine the value
for the element being modeled that particular time.
Explain what is meant by the concept of "time compression" in simulation modeling. -
Answer- Correct The effects of OM policies over many months or years can be obtained
by computer simulation in a short time.
Explain what is meant by the statement: "simulation is not limited to using the standard
probability distributions." - Answer- Correct "Standard models" include normal, binomial,
beta, uniform, Poisson, exponential, and other probability distributions. Each has a
specific set of assumptions and parameters. Real-world (empirical) systems can have
any distribution imaginable. Simulation can mimic these real-world distributions by the
use of random number intervals based on real-world behavior, and can therefore
generate more realistic models than would occur if a standard model were used in place
of a system-specific one.
From a portion of a probability distribution, you read that P(demand = 0) is 0.05 and
P(demand = 1) is 0.10. The cumulative probability for demand = 1 would be which of the
following? - Answer- .15
From a portion of a probability distribution, you read that P(demand = 0) is 0.05,
P(demand = 1) is 0.10, and P(demand = 2) is 0.20. What are the two-digit random
number intervals for this distribution beginning with 01? - Answer- Correct 01 through
05, 06 through 15, and 16 through 35
From a portion of a probability distribution, you read that P(demand = 0) is 0.25, and
P(demand = 1) is 0.30. What are the random number intervals for this distribution
beginning with 01? - Answer- Correct 01 through 25, and 26 through 55
, From a portion of a probability distribution, you read that P(demand = 1) is 0.05,
P(demand = 2) is 0.15, and P(demand = 3) is .20. The cumulative probability for
demand = 3 would be which of the following? - Answer- Correct Cannot be determined
from the information given.
Historical records on a certain product indicate the following behavior for demand. The
data represent the 288 days that the business was open during 2000. Convert these
data into random number intervals. (Round each probability used to 2 decimal places,
e.g., 0.36.)
demand in cases: 7,8,9,10,11,12
number of occuranc: 52,9,14,39,72,102 - Answer- demand in cases: 7,8,9,10,11,12
number of occuranc: 52,9,14,39,72,102
probablility: .18, .03, .05. .14, .25, .35
cumulative probab:
.18, .21, .26, .40, .65, 1.0
random number intercals:
01-18, 19-21, 22-26, 41-65, 66,00
Identify five applications of simulation. - Answer- Correct The five applications of
simulation can be picked from a list in Table F.1. Some examples are: traffic-light timing,
bus scheduling, plant layout, production scheduling, inventory planning, and assembly-
line balancing.
Identify the seven steps involved in using simulation. - Answer- 1. Define the problem.
2. Introduce the important variables associated with the problem.
3. Construct a numerical model.
4. Set up possible courses of action for testing by specifying values of variables.
5. Run the experiment.
6. Consider the results (possibly modifying the model or changing data inputs).
7. Decide what course of action to take.
Identify, in order, the five steps required to implement the Monte Carlo simulation
technique. - Answer- Correct (1) Setting up a probability distribution for important
variables. (2) Building a cumulative probability distribution for each variable. (3)
Establishing an interval of random numbers for each variable. (4) Generating random
numbers. (5) Actually simulating a series of trials.
"Time compression" and the ability to pose "what-if?" questions are elements of: -
Answer- Correct the advantages of simulation.
