Deck 26: Vehicle Routing and Scheduling

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Question
Simulation is the attempt to duplicate the features, appearance, and characteristics of a real system, usually by means of a computerized model.
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Question
By starting random number intervals at 01, not 00, the top of each range is the cumulative probability.
Question
Simulation models are inexpensive to design and use.
Question
Simulation models that are based on the generation of random numbers may fail to give the same solution in repeated use to any particular problem.
Question
All forms of simulation are based on probability or chance.
Question
Simulation allows managers to test the effects of major policy decisions on real-life systems without disturbing the real system.
Question
Virtually all large-scale simulations take place on computers, but small simulations can be conducted by hand.
Question
One reason for using simulation rather than an analytical model in an inventory problem is that the simulation is able to handle probabilistic demand and lead times.
Question
Results of simulation experiments with large numbers of trials or long experimental runs will generally be better than those with fewer trials or shorter experimental runs.
Question
One effective use of simulation is to study problems for which the mathematical models of operations management are not realistic enough.
Question
Simulation provides optimal solutions to problems.
Question
The idea behind simulation is threefold: (1) to imitate a real-world situation mathematically, (2) then to study its properties and operating characteristics, and (3) finally to draw conclusions and make action decisions based on the results of the simulation.
Question
Simulation is usually capable of producing a more appropriate answer to a complex problem than can be obtained from a mathematical model.
Question
In most real-world inventory problems, lead time and demand vary in ways that make simulation a necessity because mathematical modeling is extremely difficult.
Question
A simulation is "Monte Carlo" when the elements of a system being simulated exhibit chance in their behavior.
Question
A reason for the use of simulation in queuing is that the four standard queuing models do not allow for unusual arrival and service distributions.
Question
Like mathematical and analytical models, simulation is restricted to using the standard probability distributions.
Question
A simulation model is designed to arrive at a single specific numerical answer to a given problem.
Question
Random number intervals are based on cumulative probability distributions.
Question
Simulation has numerous applications in modern business, but few of these are in the area of operations.
Question
The seven steps in the use of simulation include all but which of the following?

A) define the problem
B) construct a mathematical model
C) introduce important variables associated with the problem
D) find the optimal solution
E) run the experiment
Question
One of the advantages of simulation is that

A) it is much less expensive than a mathematical solution
B) it always generates a more accurate solution than a mathematical solution
C) the policy changes may be tried out without disturbing the real-life system
D) model development is less time consuming than for mathematical models
E) model solutions are transferable to a wide variety of problems
Question
One of the disadvantages of simulation is that it

A) does not allow for very complex problem solutions
B) is not very flexible
C) is a trial-and-error approach that may produce different solutions in different runs
D) is very limited in the type of probability distribution that can be used
E) interferes with the production systems while the program is being run
Question
Which of the following statements regarding simulation is true?

A) Simulation can be physical or mathematical.
B) Simulation has numerous areas of application in operations.
C) Simulation attempts to duplicate a real system.
D) Monte Carlo simulation is a chance-based mathematical model of a real system.
E) All of these are true.
Question
Which of the following are advantages to simulation? I. Time compression
II. What-if questions are possible
III. Flexibility
IV. Trial and Error approach
V. Input must be user generated

A) I, III, V
B) I, II, V
C) II, III, IV, V
D) I, II, IV, V
E) I, II, III
Question
The Las Vegas method is a simulation technique that uses random elements when chance exists in their behavior.
Question
Which of the following is not a disadvantage to simulation?

A) Time compression
B) Expensive, can take months to develop
C) Trial and error approach
D) All input must be user generated
E) All of these are disadvantages to simulation
Question
Which of the following is true regarding simulation?

A) If an analytical model can't solve a problem, neither can a simulation.
B) Simulation can only be done by computer.
C) Monte Carlo simulation requires the use of random numbers.
D) Simulation models are inexpensive.
E) All of the above are true.
Question
One of the disadvantages of simulation is that it

A) does not allow for very complex problem solutions
B) is not very flexible
C) may be very expensive and time-consuming to develop
D) is very limited in the type of probability distribution that can be used
E) interferes with the production systems while the program is being run
Question
The effects of OM policies over many months or years can be obtained by computer simulation in a short time. This phenomenon is referred to as

A) time suppression
B) time suspension
C) time compression
D) time inversion
E) time conversion
Question
"Time compression" and the ability to pose "what-if" questions are elements of

A) setting up a probability distribution for important variables
B) the disadvantages of simulation
C) physical simulations but not mathematical simulations
D) the advantages of simulation
E) the broad threefold idea of simulation
Question
Simulation can use any probability distribution that the user defines.
Question
Which of the following is not an application of simulation in the area of operations?

A) personnel scheduling
B) truck dispatching
C) plant (or facility) layout
D) inventory management using EOQ principles
E) inventory planning and control
Question
One of the advantages of simulation is that

A) it is much less expensive than a mathematical solution
B) it always generates a more accurate solution than a mathematical solution
C) it can study the interactive effects of individual components or variables
D) model development is less time consuming than for mathematical models
E) model solutions are transferable to a wide variety of problems
Question
One of the advantages of simulation is that

A) real-world complications can be included that most OM models cannot permit
B) it always generates a more accurate solution than a mathematical solution
C) it is a trial-and-error approach that may produce different solutions in repeated runs
D) model development is less time consuming than for mathematical models
E) model solutions are transferable to a wide variety of problems
Question
Which of the following is true regarding simulation?

A) Small problems can be done by hand.
B) Most simulations are computerized.
C) Real-world complications can be included in simulation models.
D) Simulation is most suitable where standard analytical models are too complex.
E) All of the above are true.
Question
Simulation is used for several reasons, including

A) model development is a fast process
B) it is inexpensive
C) the models are usually simple
D) it can handle large and complex real-world problems
E) it always generates optimal solutions
Question
One of the disadvantages of simulation is that it

A) does not allow for very complex problem solutions
B) produces solutions and inferences that are not usually transferable to other problems
C) cannot study the interactive effects of individual components or variables
D) is very limited in the type of probability distribution that can be used
E) interferes with the production systems while the program is being run
Question
Which of the following is not an idea behind simulation?

A) to imitate a real-world situation mathematically
B) study the properties and operating characteristics
C) draw conclusions and make decisions based on the results
D) both A and B
E) A, B, and C are all ideas behind simulation,
Question
Which of the following is true regarding the use of simulation?

A) It is always very easy to build a simulation model.
B) It is very inexpensive to use a simulation model.
C) It always yields optimum solutions.
D) It allows time-compression in testing major policy decisions.
E) Few constraints, if any, have to be considered.
Question
A distribution of service times at a waiting line indicates that service takes 12 minutes 30 percent of the time and 14 minutes 70 percent of the time. This distribution has been prepared for Monte Carlo analysis. The first four random numbers drawn are 07, 60, 77, and 49. The average service time of this simulation is

A) 12 minutes
B) 13 minutes
C) 13.5 minutes
D) 14 minutes
E) none of these
Question
A distribution of service times at a waiting line shows that service takes 6 minutes 30 percent of the time, 7 minutes 40 percent of the time, 8 minutes 20 percent of the time, and 9 minutes 10 percent of the time. This distribution has been prepared for Monte Carlo analysis. The first two random numbers drawn are 53 and 74. The simulated service times are __________ minutes, then __________ minutes.

A) 6; 7
B) 7; 7
C) 7; 8
D) 8; 9
E) Cannot determine, because no service time probability is that large.
Question
The __________ method is a simulation technique that uses random elements when chance exists in their behavior.
Question
The number of tires sold at a car garage varies randomly between 0 and 4 each hour. What set of random numbers (on the 1-100 scale would tire sales of 2 be assigned?

A) 01 through 20
B) 21 through 40
C) 41 through 60
D) 61 through 80
E) 81 through 100
Question
What is the cumulative probability distribution of the following variable? <strong>What is the cumulative probability distribution of the following variable?  </strong> A) 1 B) .5 C) 10 D) .2 E) none of the above <div style=padding-top: 35px>

A) 1
B) .5
C) 10
D) .2
E) none of the above
Question
Monte Carlo simulations applied to queuing problems have what advantage?

A) simpler
B) Arrival distribution does not need to be a Poisson distribution.
C) Unloading rates can vary randomly.
D) B and C
E) A, B, and C
Question
A distribution of service times at a waiting line indicates that service takes 6 minutes 30 percent of the time, 7 minutes 40 percent of the time, 8 minutes 20 percent of the time, and 9 minutes 10 percent of the time. In preparing this distribution for Monte Carlo analysis, the service time 8 minutes would be represented by the random number range

A) 20 through 40
B) 21 through 40
C) 70 through 90
D) 71 through 90
E) none of these
Question
Which of the following is a necessity for common EOQ methodology but not simulations

A) constant lead time
B) variable demand
C) variable holding costs
D) A and B
E) A, B and C
Question
Setting up a probability distribution, building a cumulative probability distribution, and generating random numbers are

A) necessary when the underlying probability distribution is normal
B) three of the five steps in Monte Carlo analysis
C) elements of physical simulation but not mathematical simulation
D) the three steps involved in simulating a queuing problem
E) advantages of simulation
Question
A(n) __________ is a series of digits that have been selected by a totally random process.
Question
Which of the following is not a step in running a Monte Carlo simulation?

A) setting up a probability distribution for important variables
B) building a cumulative probability distribution for each variable
C) establishing an interval of random numbers for each variable
D) generating random numbers
E) All of the above are steps in running a Monte Carlo simulation.
Question
__________ is the attempt to duplicate the features, appearance, and characteristics of a real system, usually by means of a computerized model.
Question
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. The two-digit random number intervals for this distribution beginning with 01 are

A) 01 through 05, 01 through 10, and 01 through 20
B) 00 through 04, 05 through 14, and 15 through 34
C) 01 through 05, 06 through 15, and 16 through 35
D) 00 through 04, 00 through 09, and 00 through 19
E) 01 through 06, 07 through 16, and 17 through 36
Question
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

A) 0.133
B) 0.200
C) 0.400
D) 0.600
E) cannot be determined from the information given
Question
From a portion of a probability distribution, you read that P(demand = 0) is 0.25, and P(demand = 1) is 0.30. The random number intervals for this distribution beginning with 01 are

A) 01 through 25, and 26 through 30
B) 01 through 25, and 01 through 30
C) 01 through 25, and 26 through 55
D) 00 through 25, and 26 through 55
E) 00 through 25, and 26 through 30
Question
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

A) 0.05
B) 0.075
C) 0.10
D) 0.15
E) cannot be determined
Question
A distribution of lead times in an inventory problem indicates that lead time was 1 day 20 percent of the time, 2 days 30 percent of the time, 3 days 30 percent of the time, and. 4 days 20 percent of the time. This distribution has been prepared for Monte Carlo analysis. The first four random numbers drawn are 06, 63, 57, and 02. The average lead time of this simulation is

A) 1.75 days
B) 2 days
C) 3 days
D) 3.5 days
E) none of these
Question
A distribution of service times at a waiting line indicates that service takes 12 minutes 30 percent of the time and 14 minutes 70 percent of the time. In preparing this distribution for Monte Carlo analysis, the service time 13 minutes would be represented by the random number range

A) 00 through 29
B) 01 through 30
C) 30 through 99
D) 31 through 00
E) None of these; 13 minutes is not a possible outcome.
Question
Which of the following restrictions applies to queuing models but not Monte Carlo simulations?

A) Poisson distribution of arrivals
B) constant or exponential service times
C) average length of line
D) A and B
E) A, B, and C
Question
A(n) __________ is the accumulation of individual probabilities of a distribution.
Question
Explain what is meant by the concept of "time compression" in simulation modeling.
Question
The numbers used to represent each possible value or outcome in a computer simulation are referred to as __________ .
Question
A waiting-line problem that cannot be modeled by standard distributions has been simulated. The table below shows the result of a Monte Carlo simulation. (Assume that the simulation began at 8:00 a.m. and there is only one server.
A waiting-line problem that cannot be modeled by standard distributions has been simulated. The table below shows the result of a Monte Carlo simulation. (Assume that the simulation began at 8:00 a.m. and there is only one server.   a. What is the average waiting time in line? b. What is the average time in the system?<div style=padding-top: 35px> a. What is the average waiting time in line?
b. What is the average time in the system?
Question
Provide a small example illustrating how random numbers are used in Monte Carlo simulation.
Question
Explain what is meant by "simulation is not limited to using the standard probability distributions."
Question
Identify, in order, the five steps required to implement the Monte Carlo simulation technique.
Question
A distribution of service times at a waiting line shows that service takes 6 minutes 40 percent of the time, 7 minutes 30 percent of the time, 8 minutes 20 percent of the time, and 9 minutes 10 percent of the time. Prepare the probability distribution, the cumulative probability distribution, and the random number intervals for this problem. The first five random numbers are 37, 69, 53, 80, and 60. What is the average service time of this simulation run?
Question
A distribution of service times at a waiting line shows that service takes 6 minutes 40 percent of the time, 7 minutes 30 percent of the time, 8 minutes 20 percent of the time, and 9 minutes 10 percent of the time. Prepare the probability distribution, the cumulative probability distribution, and the random number intervals for this problem.
Question
Identify the seven steps involved in using simulation.
Question
What are the advantages and disadvantages of simulation models?
Question
Define simulation.
Question
What is the Monte Carlo method?
Question
Would you simulate a problem for which there is an exact mathematical model already?
Question
Explain the difference between random numbers and random number intervals.
Question
Identify five applications of simulation.
Question
A warehouse manager needs to simulate the demand placed on a product that does not fit standard models. The concept being measured is "demand during lead time," where both lead time and daily demand are variable. The historical record for this product suggests the following probability distribution. Convert this distribution into random number intervals.
A warehouse manager needs to simulate the demand placed on a product that does not fit standard models. The concept being measured is demand during lead time, where both lead time and daily demand are variable. The historical record for this product suggests the following probability distribution. Convert this distribution into random number intervals.  <div style=padding-top: 35px>
Question
The effects of OM policies over many months or years can be obtained by computer simulation in a short time. This phenomenon is referred to as __________ .
Question
A waiting-line problem that cannot be modeled by standard distributions has been simulated. The table below shows the result of a Monte Carlo simulation. (Assume that the simulation began at 8:00 a.m. and there is only one server.) Why do you think this problem does not fit the standard distribution for waiting lines? Explain briefly how a Monte Carlo simulation might work where analytical models cannot.
A waiting-line problem that cannot be modeled by standard distributions has been simulated. The table below shows the result of a Monte Carlo simulation. (Assume that the simulation began at 8:00 a.m. and there is only one server.) Why do you think this problem does not fit the standard distribution for waiting lines? Explain briefly how a Monte Carlo simulation might work where analytical models cannot.  <div style=padding-top: 35px>
Question
State the three-fold idea behind simulation.
Question
Explain how Monte Carlo simulation uses random numbers.
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Deck 26: Vehicle Routing and Scheduling
1
Simulation is the attempt to duplicate the features, appearance, and characteristics of a real system, usually by means of a computerized model.
True
2
By starting random number intervals at 01, not 00, the top of each range is the cumulative probability.
True
3
Simulation models are inexpensive to design and use.
False
4
Simulation models that are based on the generation of random numbers may fail to give the same solution in repeated use to any particular problem.
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k this deck
5
All forms of simulation are based on probability or chance.
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6
Simulation allows managers to test the effects of major policy decisions on real-life systems without disturbing the real system.
Unlock Deck
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k this deck
7
Virtually all large-scale simulations take place on computers, but small simulations can be conducted by hand.
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
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k this deck
8
One reason for using simulation rather than an analytical model in an inventory problem is that the simulation is able to handle probabilistic demand and lead times.
Unlock Deck
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Unlock Deck
k this deck
9
Results of simulation experiments with large numbers of trials or long experimental runs will generally be better than those with fewer trials or shorter experimental runs.
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10
One effective use of simulation is to study problems for which the mathematical models of operations management are not realistic enough.
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11
Simulation provides optimal solutions to problems.
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12
The idea behind simulation is threefold: (1) to imitate a real-world situation mathematically, (2) then to study its properties and operating characteristics, and (3) finally to draw conclusions and make action decisions based on the results of the simulation.
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13
Simulation is usually capable of producing a more appropriate answer to a complex problem than can be obtained from a mathematical model.
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k this deck
14
In most real-world inventory problems, lead time and demand vary in ways that make simulation a necessity because mathematical modeling is extremely difficult.
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k this deck
15
A simulation is "Monte Carlo" when the elements of a system being simulated exhibit chance in their behavior.
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16
A reason for the use of simulation in queuing is that the four standard queuing models do not allow for unusual arrival and service distributions.
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17
Like mathematical and analytical models, simulation is restricted to using the standard probability distributions.
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18
A simulation model is designed to arrive at a single specific numerical answer to a given problem.
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19
Random number intervals are based on cumulative probability distributions.
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20
Simulation has numerous applications in modern business, but few of these are in the area of operations.
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21
The seven steps in the use of simulation include all but which of the following?

A) define the problem
B) construct a mathematical model
C) introduce important variables associated with the problem
D) find the optimal solution
E) run the experiment
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Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
22
One of the advantages of simulation is that

A) it is much less expensive than a mathematical solution
B) it always generates a more accurate solution than a mathematical solution
C) the policy changes may be tried out without disturbing the real-life system
D) model development is less time consuming than for mathematical models
E) model solutions are transferable to a wide variety of problems
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
23
One of the disadvantages of simulation is that it

A) does not allow for very complex problem solutions
B) is not very flexible
C) is a trial-and-error approach that may produce different solutions in different runs
D) is very limited in the type of probability distribution that can be used
E) interferes with the production systems while the program is being run
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
24
Which of the following statements regarding simulation is true?

A) Simulation can be physical or mathematical.
B) Simulation has numerous areas of application in operations.
C) Simulation attempts to duplicate a real system.
D) Monte Carlo simulation is a chance-based mathematical model of a real system.
E) All of these are true.
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Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
25
Which of the following are advantages to simulation? I. Time compression
II. What-if questions are possible
III. Flexibility
IV. Trial and Error approach
V. Input must be user generated

A) I, III, V
B) I, II, V
C) II, III, IV, V
D) I, II, IV, V
E) I, II, III
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26
The Las Vegas method is a simulation technique that uses random elements when chance exists in their behavior.
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27
Which of the following is not a disadvantage to simulation?

A) Time compression
B) Expensive, can take months to develop
C) Trial and error approach
D) All input must be user generated
E) All of these are disadvantages to simulation
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k this deck
28
Which of the following is true regarding simulation?

A) If an analytical model can't solve a problem, neither can a simulation.
B) Simulation can only be done by computer.
C) Monte Carlo simulation requires the use of random numbers.
D) Simulation models are inexpensive.
E) All of the above are true.
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
29
One of the disadvantages of simulation is that it

A) does not allow for very complex problem solutions
B) is not very flexible
C) may be very expensive and time-consuming to develop
D) is very limited in the type of probability distribution that can be used
E) interferes with the production systems while the program is being run
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
30
The effects of OM policies over many months or years can be obtained by computer simulation in a short time. This phenomenon is referred to as

A) time suppression
B) time suspension
C) time compression
D) time inversion
E) time conversion
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
31
"Time compression" and the ability to pose "what-if" questions are elements of

A) setting up a probability distribution for important variables
B) the disadvantages of simulation
C) physical simulations but not mathematical simulations
D) the advantages of simulation
E) the broad threefold idea of simulation
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
32
Simulation can use any probability distribution that the user defines.
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33
Which of the following is not an application of simulation in the area of operations?

A) personnel scheduling
B) truck dispatching
C) plant (or facility) layout
D) inventory management using EOQ principles
E) inventory planning and control
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
34
One of the advantages of simulation is that

A) it is much less expensive than a mathematical solution
B) it always generates a more accurate solution than a mathematical solution
C) it can study the interactive effects of individual components or variables
D) model development is less time consuming than for mathematical models
E) model solutions are transferable to a wide variety of problems
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
35
One of the advantages of simulation is that

A) real-world complications can be included that most OM models cannot permit
B) it always generates a more accurate solution than a mathematical solution
C) it is a trial-and-error approach that may produce different solutions in repeated runs
D) model development is less time consuming than for mathematical models
E) model solutions are transferable to a wide variety of problems
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
36
Which of the following is true regarding simulation?

A) Small problems can be done by hand.
B) Most simulations are computerized.
C) Real-world complications can be included in simulation models.
D) Simulation is most suitable where standard analytical models are too complex.
E) All of the above are true.
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
37
Simulation is used for several reasons, including

A) model development is a fast process
B) it is inexpensive
C) the models are usually simple
D) it can handle large and complex real-world problems
E) it always generates optimal solutions
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
38
One of the disadvantages of simulation is that it

A) does not allow for very complex problem solutions
B) produces solutions and inferences that are not usually transferable to other problems
C) cannot study the interactive effects of individual components or variables
D) is very limited in the type of probability distribution that can be used
E) interferes with the production systems while the program is being run
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
39
Which of the following is not an idea behind simulation?

A) to imitate a real-world situation mathematically
B) study the properties and operating characteristics
C) draw conclusions and make decisions based on the results
D) both A and B
E) A, B, and C are all ideas behind simulation,
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40
Which of the following is true regarding the use of simulation?

A) It is always very easy to build a simulation model.
B) It is very inexpensive to use a simulation model.
C) It always yields optimum solutions.
D) It allows time-compression in testing major policy decisions.
E) Few constraints, if any, have to be considered.
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
41
A distribution of service times at a waiting line indicates that service takes 12 minutes 30 percent of the time and 14 minutes 70 percent of the time. This distribution has been prepared for Monte Carlo analysis. The first four random numbers drawn are 07, 60, 77, and 49. The average service time of this simulation is

A) 12 minutes
B) 13 minutes
C) 13.5 minutes
D) 14 minutes
E) none of these
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
42
A distribution of service times at a waiting line shows that service takes 6 minutes 30 percent of the time, 7 minutes 40 percent of the time, 8 minutes 20 percent of the time, and 9 minutes 10 percent of the time. This distribution has been prepared for Monte Carlo analysis. The first two random numbers drawn are 53 and 74. The simulated service times are __________ minutes, then __________ minutes.

A) 6; 7
B) 7; 7
C) 7; 8
D) 8; 9
E) Cannot determine, because no service time probability is that large.
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k this deck
43
The __________ method is a simulation technique that uses random elements when chance exists in their behavior.
Unlock Deck
Unlock for access to all 92 flashcards in this deck.
Unlock Deck
k this deck
44
The number of tires sold at a car garage varies randomly between 0 and 4 each hour. What set of random numbers (on the 1-100 scale would tire sales of 2 be assigned?

A) 01 through 20
B) 21 through 40
C) 41 through 60
D) 61 through 80
E) 81 through 100
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45
What is the cumulative probability distribution of the following variable? <strong>What is the cumulative probability distribution of the following variable?  </strong> A) 1 B) .5 C) 10 D) .2 E) none of the above

A) 1
B) .5
C) 10
D) .2
E) none of the above
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46
Monte Carlo simulations applied to queuing problems have what advantage?

A) simpler
B) Arrival distribution does not need to be a Poisson distribution.
C) Unloading rates can vary randomly.
D) B and C
E) A, B, and C
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47
A distribution of service times at a waiting line indicates that service takes 6 minutes 30 percent of the time, 7 minutes 40 percent of the time, 8 minutes 20 percent of the time, and 9 minutes 10 percent of the time. In preparing this distribution for Monte Carlo analysis, the service time 8 minutes would be represented by the random number range

A) 20 through 40
B) 21 through 40
C) 70 through 90
D) 71 through 90
E) none of these
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48
Which of the following is a necessity for common EOQ methodology but not simulations

A) constant lead time
B) variable demand
C) variable holding costs
D) A and B
E) A, B and C
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49
Setting up a probability distribution, building a cumulative probability distribution, and generating random numbers are

A) necessary when the underlying probability distribution is normal
B) three of the five steps in Monte Carlo analysis
C) elements of physical simulation but not mathematical simulation
D) the three steps involved in simulating a queuing problem
E) advantages of simulation
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50
A(n) __________ is a series of digits that have been selected by a totally random process.
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51
Which of the following is not a step in running a Monte Carlo simulation?

A) setting up a probability distribution for important variables
B) building a cumulative probability distribution for each variable
C) establishing an interval of random numbers for each variable
D) generating random numbers
E) All of the above are steps in running a Monte Carlo simulation.
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52
__________ is the attempt to duplicate the features, appearance, and characteristics of a real system, usually by means of a computerized model.
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53
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. The two-digit random number intervals for this distribution beginning with 01 are

A) 01 through 05, 01 through 10, and 01 through 20
B) 00 through 04, 05 through 14, and 15 through 34
C) 01 through 05, 06 through 15, and 16 through 35
D) 00 through 04, 00 through 09, and 00 through 19
E) 01 through 06, 07 through 16, and 17 through 36
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54
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

A) 0.133
B) 0.200
C) 0.400
D) 0.600
E) cannot be determined from the information given
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55
From a portion of a probability distribution, you read that P(demand = 0) is 0.25, and P(demand = 1) is 0.30. The random number intervals for this distribution beginning with 01 are

A) 01 through 25, and 26 through 30
B) 01 through 25, and 01 through 30
C) 01 through 25, and 26 through 55
D) 00 through 25, and 26 through 55
E) 00 through 25, and 26 through 30
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56
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

A) 0.05
B) 0.075
C) 0.10
D) 0.15
E) cannot be determined
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57
A distribution of lead times in an inventory problem indicates that lead time was 1 day 20 percent of the time, 2 days 30 percent of the time, 3 days 30 percent of the time, and. 4 days 20 percent of the time. This distribution has been prepared for Monte Carlo analysis. The first four random numbers drawn are 06, 63, 57, and 02. The average lead time of this simulation is

A) 1.75 days
B) 2 days
C) 3 days
D) 3.5 days
E) none of these
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58
A distribution of service times at a waiting line indicates that service takes 12 minutes 30 percent of the time and 14 minutes 70 percent of the time. In preparing this distribution for Monte Carlo analysis, the service time 13 minutes would be represented by the random number range

A) 00 through 29
B) 01 through 30
C) 30 through 99
D) 31 through 00
E) None of these; 13 minutes is not a possible outcome.
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59
Which of the following restrictions applies to queuing models but not Monte Carlo simulations?

A) Poisson distribution of arrivals
B) constant or exponential service times
C) average length of line
D) A and B
E) A, B, and C
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60
A(n) __________ is the accumulation of individual probabilities of a distribution.
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61
Explain what is meant by the concept of "time compression" in simulation modeling.
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62
The numbers used to represent each possible value or outcome in a computer simulation are referred to as __________ .
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63
A waiting-line problem that cannot be modeled by standard distributions has been simulated. The table below shows the result of a Monte Carlo simulation. (Assume that the simulation began at 8:00 a.m. and there is only one server.
A waiting-line problem that cannot be modeled by standard distributions has been simulated. The table below shows the result of a Monte Carlo simulation. (Assume that the simulation began at 8:00 a.m. and there is only one server.   a. What is the average waiting time in line? b. What is the average time in the system? a. What is the average waiting time in line?
b. What is the average time in the system?
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64
Provide a small example illustrating how random numbers are used in Monte Carlo simulation.
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65
Explain what is meant by "simulation is not limited to using the standard probability distributions."
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66
Identify, in order, the five steps required to implement the Monte Carlo simulation technique.
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67
A distribution of service times at a waiting line shows that service takes 6 minutes 40 percent of the time, 7 minutes 30 percent of the time, 8 minutes 20 percent of the time, and 9 minutes 10 percent of the time. Prepare the probability distribution, the cumulative probability distribution, and the random number intervals for this problem. The first five random numbers are 37, 69, 53, 80, and 60. What is the average service time of this simulation run?
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68
A distribution of service times at a waiting line shows that service takes 6 minutes 40 percent of the time, 7 minutes 30 percent of the time, 8 minutes 20 percent of the time, and 9 minutes 10 percent of the time. Prepare the probability distribution, the cumulative probability distribution, and the random number intervals for this problem.
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69
Identify the seven steps involved in using simulation.
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70
What are the advantages and disadvantages of simulation models?
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71
Define simulation.
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72
What is the Monte Carlo method?
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73
Would you simulate a problem for which there is an exact mathematical model already?
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74
Explain the difference between random numbers and random number intervals.
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75
Identify five applications of simulation.
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76
A warehouse manager needs to simulate the demand placed on a product that does not fit standard models. The concept being measured is "demand during lead time," where both lead time and daily demand are variable. The historical record for this product suggests the following probability distribution. Convert this distribution into random number intervals.
A warehouse manager needs to simulate the demand placed on a product that does not fit standard models. The concept being measured is demand during lead time, where both lead time and daily demand are variable. The historical record for this product suggests the following probability distribution. Convert this distribution into random number intervals.
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77
The effects of OM policies over many months or years can be obtained by computer simulation in a short time. This phenomenon is referred to as __________ .
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78
A waiting-line problem that cannot be modeled by standard distributions has been simulated. The table below shows the result of a Monte Carlo simulation. (Assume that the simulation began at 8:00 a.m. and there is only one server.) Why do you think this problem does not fit the standard distribution for waiting lines? Explain briefly how a Monte Carlo simulation might work where analytical models cannot.
A waiting-line problem that cannot be modeled by standard distributions has been simulated. The table below shows the result of a Monte Carlo simulation. (Assume that the simulation began at 8:00 a.m. and there is only one server.) Why do you think this problem does not fit the standard distribution for waiting lines? Explain briefly how a Monte Carlo simulation might work where analytical models cannot.
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79
State the three-fold idea behind simulation.
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80
Explain how Monte Carlo simulation uses random numbers.
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