Exam 23: Simulation
Exam 1: Operations and Productivity134 Questions
Exam 2: Operations Strategy in a Global Environment145 Questions
Exam 3: Project Management131 Questions
Exam 4: Forecasting151 Questions
Exam 5: Design of Goods and Services136 Questions
Exam 6: Managing Quality139 Questions
Exam 7: Process Strategy and Sustainability141 Questions
Exam 8: Location Strategies149 Questions
Exam 9: Layout Strategies171 Questions
Exam 10: Human Resources, Job Design, and Work Measurement202 Questions
Exam 11: Supply-Chain Management152 Questions
Exam 12: Inventory Management178 Questions
Exam 13: Aggregate Planning144 Questions
Exam 14: Material Requirements Planning Mrp and Erp184 Questions
Exam 15: Short-Term Scheduling149 Questions
Exam 16: Lean Operations147 Questions
Exam 17: Maintenance and Reliability139 Questions
Exam 18: Decision-Making Tools107 Questions
Exam 19: Linear Programming110 Questions
Exam 20: Transportation Models104 Questions
Exam 21: Waiting-Line Models145 Questions
Exam 22: Learning Curves121 Questions
Exam 23: Simulation102 Questions
Exam 24: Supply Chain Management Analytics65 Questions
Exam 25: Sustainability in the Supply Chain11 Questions
Exam 26: Statistical Process Control166 Questions
Exam 27: Capacity and Constraint Management117 Questions
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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.
(True/False)
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Complete the following table in preparation for a Monte Carlo simulation.
Demand Probability Cumulative Probability Interval of Random Numbers 1 01-20 2 21-25 3 26-50 4 51-80 5 81-00
(Essay)
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A waiting-line problem that cannot be modelled 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.
Customer Number Arrival Time Service Time Service Ends 1 8:06 2 8:08 2 8:07 10 8:18 3 8:12 10 8:28 4 8:24 11 8:39 5 8:30 5 8:44 a. What is the average waiting time in line?
b. What is the average time in the system?
(Essay)
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Would you simulate a problem for which there is an exact mathematical model already?
(Essay)
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Provide a small example illustrating how random numbers are used in Monte Carlo simulation.
(Essay)
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Which of the following is not a step in running a Monte Carlo simulation?
(Multiple Choice)
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Complete the following table in preparation for a Monte Carlo simulation. The expected demand is 8.
Demand Probability Cumulative Probability Interval of Random Numbers 0 .2 2 21-40 3 4 4 85-100
(Essay)
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The seven steps in the use of simulation include all but which of the following?
(Multiple Choice)
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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?
(Multiple Choice)
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Which of the following statements regarding simulation is true?
(Multiple Choice)
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Virtually all large-scale simulations take place on computers, but small simulations can be conducted by hand.
(True/False)
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A distribution of service times at a waiting line indicates that service takes 6 minutes 30% of the time, 7 minutes 40% of the time, 8 minutes 20% of the time, and 9 minutes 10% of the time. In preparing this distribution for Monte Carlo analysis, the service time 8 minutes would be represented by the random number range
(Multiple Choice)
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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 ________.
(Short Answer)
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"Time compression" and the ability to pose "what-if" questions are elements of
(Multiple Choice)
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