Question 1

Monte Carlo simulations applied to queuing problems have what advantage?

Accepted Answer

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 
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 2

A(n) __________ is the accumulation of individual probabilities of a distribution.

Accepted Answer

cumulative

Question 3

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. Prepare the probability distribution, the cumulative probability distribution, and the random number intervals for this problem. The first six random numbers were 99, 29, 27, 75, 89, and 78. What is the average service time for this simulation run?

Accepted Answer

@#IMG-DLM& The average service

Question 4

Identify five applications of simulation.

Accepted Answer

The five applications of simulation can

Question 5

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

Accepted Answer

A)  I, III, V 
B)  I, II, V 
C)  II, III, IV, V 
D)  I, II, IV, V 
E)  I, II, III 
A)  I, III, V 
B)  I, II, V 
C)  II, III, IV, V 
D)  I, II, IV, V 
E)  I, II, III

Question 6

Provide a small example illustrating how random numbers are used in Monte Carlo simulation.

Accepted Answer

For example, demand can be 0, 40% of the

Question 7

Explain what is meant by the concept of "time compression" in simulation modeling.

Accepted Answer

The effects of OM policies ove

Question 8

The Las Vegas method is a simulation technique that uses random elements when chance exists in their behavior.

Accepted Answer

A) True 
 B)False

Question 9

Simulation is usually capable of producing a more appropriate answer to a complex problem than can be obtained from a mathematical model.

Accepted Answer

A) True 
 B)False

Question 10

A(n) __________ is a series of digits that have been selected by a totally random process.

Accepted Answer

The answer of A(n) __________ is a series of digits...

Question 11

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?

Accepted Answer

@#IMG-DLM& The average service

Question 12

Identify, in order, the five steps required to implement the Monte Carlo simulation technique.

Accepted Answer

The steps of the Monte Carlo simulation

Question 13

Identify the seven steps involved in using simulation.

Accepted Answer

1. Define the problem.
2. Introduce the

Question 14

Which of the following is not an application of simulation in the area of operations?

Accepted Answer

A)  personnel scheduling 
B)  truck dispatching 
C)  plant (or facility) layout 
D)  inventory management using EOQ principles 
E)  inventory planning and control 
A)  personnel scheduling 
B)  truck dispatching 
C)  plant (or facility) layout 
D)  inventory management using EOQ principles 
E)  inventory planning and control

Question 15

Which of the following is true regarding simulation?

Accepted Answer

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. 
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 16

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.

Accepted Answer

The answer of A distribution of service times at a...

Question 17

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?

Accepted Answer

A)  01 through 20 
B)  21 through 40 
C)  41 through 60 
D)  61 through 80 
E)  81 through 100 
A)  01 through 20 
B)  21 through 40 
C)  41 through 60 
D)  61 through 80 
E)  81 through 100

Question 18

Complete the following table in preparation for a Monte Carlo simulation. The expected demand is 3.52.

Accepted Answer

@#IMG-DLM& Students should have only moderate diff

Question 19

The lunch counter at a small restaurant has difficulty handling the lunch business. Currently, there is only one cashier in a single-channel, single-phase system. The restaurant has collected information on the interarrival time, and service time distributions from past lunch hours. They are represented in the tables below. Use the following two-digit random numbers given below to simulate 10 customers through the checkout system. What is the average time in line, and average time in system? (Set first arrival time to the interarrival time generated by first random number.
   Random numbers for interarrival times: 32, 73, 41, 38, 73, 01, 09, 64, 34, 44
Random numbers of service times: 84, 55, 25, 71, 34, 57, 50, 44, 95, 64

Accepted Answer

@#IMG-DLM& @#IMG-DLM& Average time in li

Question 20

The seven steps in the use of simulation include all but which of the following?

Accepted Answer

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 
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

Exam 26: Vehicle Routing and Scheduling

Monte Carlo simulations applied to queuing problems have what advantage?

A(n) __________ is the accumulation of individual probabilities of a distribution.

Identify five applications of simulation.

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

Provide a small example illustrating how random numbers are used in Monte Carlo simulation.

Explain what is meant by the concept of "time compression" in simulation modeling.

The Las Vegas method is a simulation technique that uses random elements when chance exists in their behavior.

Simulation is usually capable of producing a more appropriate answer to a complex problem than can be obtained from a mathematical model.

A(n) __________ is a series of digits that have been selected by a totally random process.

Identify, in order, the five steps required to implement the Monte Carlo simulation technique.

Identify the seven steps involved in using simulation.

Which of the following is not an application of simulation in the area of operations?

Which of the following is true regarding simulation?

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?

Complete the following table in preparation for a Monte Carlo simulation. The expected demand is 3.52.

The seven steps in the use of simulation include all but which of the following?

Operations and Productivity

Operations Strategy in a Global Environment

Project Management

Forecasting

Design of Goods and Services

Managing Quality

Process Strategy

Location Strategies

Layout Strategies

Human Resources, Job Design, and Work Measurement

Supply-Chain Management

Inventory Management

Aggregate Planning

Material Requirements Planning Mrp and Erp

Short-Term Scheduling

Just-In-Time and Lean Options

Maintenance and Reliability

Statistical Tools for Managers

Acceptance Sampling

The Simplex Method of Linear Programming

The Modi and Vam Methods of Solving Transportation Problems

Vehicle Routing and Scheduling

Managing Quality

Process Strategy

Supply-Chain Management

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