Question 1

Using simulation to perform risk analysis is like playing out many what-if scenarios by randomly generating values for the probabilistic inputs.

Accepted Answer

A) True 
 B)False

Question 2

Computer-generated random numbers are normally distributed over the interval from 0 to 1.

Accepted Answer

A) True 
 B)False

Question 3

A table of uniformly distributed random numbers should be read

Accepted Answer

A) from left to right. 
B) from top to bottom. 
C) diagonally,starting from the top left corner and moving to the bottom right. 
D) in any consistent sequence. 
A) from left to right. 
B) from top to bottom. 
C) diagonally,starting from the top left corner and moving to the bottom right. 
D) in any consistent sequence.

Question 4

Computer-generated random numbers are not technically random.

Accepted Answer

A) True 
 B)False

Question 5

A quantity that is difficult to measure with certainty is called a

Accepted Answer

A) risk analysis. 
B) project determinant. 
C) probabilistic input. 
D) profit/loss process. 
A) risk analysis. 
B) project determinant. 
C) probabilistic input. 
D) profit/loss process.

Question 6

In order to verify a simulation model

Accepted Answer

A) compare results from several simulation languages. 
B) be sure that the procedures for calculations are logically correct. 
C) confirm that the model accurately represents the real system. 
D) run the model long enough to overcome initial start-up results. 
A) compare results from several simulation languages. 
B) be sure that the procedures for calculations are logically correct. 
C) confirm that the model accurately represents the real system. 
D) run the model long enough to overcome initial start-up results.

Question 7

The process of generating probabilistic inputs and computing the value of the output is called

Accepted Answer

A) simulation. 
B) verification. 
C) validation. 
D) implementation. 
A) simulation. 
B) verification. 
C) validation. 
D) implementation.

Question 8

The degree of risk is associated with the probability or magnitude of loss.

Accepted Answer

A) True 
 B)False

Question 9

The drying rate in an industrial process is dependent on many factors and varies according to the following distribution.
   
a.Compute the mean drying time.
b.Using these random numbers,simulate the drying time for 12 processes.
   
c.What is the average drying time for the 10 processes you simulated?

Accepted Answer

a.4.82b.

Question 10

Verification is the process of ensuring that the simulation model provides an accurate representation of the real system.

Accepted Answer

A) True 
 B)False

Question 11

Simulation models that must take into account how the system changes or evolves over time are referred to as dynamic simulation models.

Accepted Answer

A) True 
 B)False

Question 12

The time required to set up lighting for a portrait studio is uniformly distributed between 12 and 20 minutes.Use the following random numbers to generate the setup time for 10 customers.

Accepted Answer

The answer of The time required to set up lighting...

Question 13

Computer-generated random numbers are normally distributed.

Accepted Answer

A) True 
 B)False

Question 14

A discrete-event simulation reviews the status of the system periodically,whether or not an event occurs.

Accepted Answer

A) True 
 B)False

Question 15

An airline reservation system first asks customers whether they want to schedule a domestic or an international flight.Sixty-five percent of the reservations are for domestic flights.The time distribution of advance sales is also important,and it is given below.
   
a.Place the appropriate random number ranges in the tables above.
b.Set up and perform a simulation for three customers.Determine whether they want a domestic or international flight,and how far in advance the reservation is being made.Use random numbers from this list: .632 .715 .998 .671 .744 .021

Accepted Answer

The answer of An airline reservation system first asks customers...

Question 16

In a Monte Carlo simulation,each simulation trial is dependent upon the result of a previous trial.

Accepted Answer

A) True 
 B)False

Question 17

For any waiting line system, (Average number of units in waiting line)= (Total waiting time)divided by (Total time of simulation).

Accepted Answer

A) True 
 B)False

Question 18

In comparing different policies using simulation,one should use the same set of random numbers whenever possible.

Accepted Answer

A) True 
 B)False

Question 19

Which of the following statements is INCORRECT regarding the advantages of simulation?

Accepted Answer

A) Simulation is relatively easy to explain and understand. 
B) Simulation guarantees an optimal solution. 
C) Simulation models are flexible. 
D) A simulation model provides a convenient experimental laboratory for the real system. 
A) Simulation is relatively easy to explain and understand. 
B) Simulation guarantees an optimal solution. 
C) Simulation models are flexible. 
D) A simulation model provides a convenient experimental laboratory for the real system.

Question 20

Simulation is an excellent technique to use when a situation is too complicated to use standard analytical procedures.

Accepted Answer

A) True 
 B)False

Using simulation to perform risk analysis is like playing out many what-if scenarios by randomly generating values for the probabilistic inputs.

Computer-generated random numbers are normally distributed over the interval from 0 to 1.

A table of uniformly distributed random numbers should be read

Computer-generated random numbers are not technically random.

A quantity that is difficult to measure with certainty is called a

In order to verify a simulation model

The process of generating probabilistic inputs and computing the value of the output is called

The degree of risk is associated with the probability or magnitude of loss.

The drying rate in an industrial process is dependent on many factors and varies according to the following distribution. a.Compute the mean drying time. b.Using these random numbers,simulate the drying time for 12 processes. c.What is the average drying time for the 10 processes you simulated?

Verification is the process of ensuring that the simulation model provides an accurate representation of the real system.

Simulation models that must take into account how the system changes or evolves over time are referred to as dynamic simulation models.

The time required to set up lighting for a portrait studio is uniformly distributed between 12 and 20 minutes.Use the following random numbers to generate the setup time for 10 customers.

Computer-generated random numbers are normally distributed.

A discrete-event simulation reviews the status of the system periodically,whether or not an event occurs.

In a Monte Carlo simulation,each simulation trial is dependent upon the result of a previous trial.

For any waiting line system, (Average number of units in waiting line)= (Total waiting time)divided by (Total time of simulation).

In comparing different policies using simulation,one should use the same set of random numbers whenever possible.

Which of the following statements is INCORRECT regarding the advantages of simulation?

Simulation is an excellent technique to use when a situation is too complicated to use standard analytical procedures.

Introduction

Introduction to Probability

Probability Distributions

Decision Analysis

Utility and Game Theory

Forecasting

Introduction to Linear Programming

Lp Sensitivity Analysis and Interpretation of Solution

Linear Programming Applications

Distribution and Network Problems

Integer Linear Programming

Advanced Optimization Application

Project Scheduling: Pertcpm

Inventory Models

Waiting Line Models

Markov Processes

Filters

Exam 16: Simulation

Using simulation to perform risk analysis is like playing out many what-if scenarios by randomly generating values for the probabilistic inputs.

Computer-generated random numbers are normally distributed over the interval from 0 to 1.

A table of uniformly distributed random numbers should be read

Computer-generated random numbers are not technically random.

A quantity that is difficult to measure with certainty is called a

In order to verify a simulation model

The process of generating probabilistic inputs and computing the value of the output is called

The degree of risk is associated with the probability or magnitude of loss.

The drying rate in an industrial process is dependent on many factors and varies according to the following distribution. a.Compute the mean drying time. b.Using these random numbers,simulate the drying time for 12 processes. c.What is the average drying time for the 10 processes you simulated?

Verification is the process of ensuring that the simulation model provides an accurate representation of the real system.

Simulation models that must take into account how the system changes or evolves over time are referred to as dynamic simulation models.

The time required to set up lighting for a portrait studio is uniformly distributed between 12 and 20 minutes.Use the following random numbers to generate the setup time for 10 customers.

Computer-generated random numbers are normally distributed.

A discrete-event simulation reviews the status of the system periodically,whether or not an event occurs.

In a Monte Carlo simulation,each simulation trial is dependent upon the result of a previous trial.

For any waiting line system, (Average number of units in waiting line)= (Total waiting time)divided by (Total time of simulation).

In comparing different policies using simulation,one should use the same set of random numbers whenever possible.

Which of the following statements is INCORRECT regarding the advantages of simulation?

Simulation is an excellent technique to use when a situation is too complicated to use standard analytical procedures.

Introduction

Introduction to Probability

Probability Distributions

Decision Analysis

Utility and Game Theory

Forecasting

Introduction to Linear Programming

Lp Sensitivity Analysis and Interpretation of Solution

Linear Programming Applications

Distribution and Network Problems

Integer Linear Programming

Advanced Optimization Application

Project Scheduling: Pertcpm

Inventory Models

Waiting Line Models

Markov Processes

Filters