Exam 22: Simulation

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A disadvantage of simulation models is that the structuring is highly dependent on the expertise of the modeler.

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A local legal aid office provides basic legal assistance to walk?in clients. The historical arrival frequency is as shown below: Clients Arriving Relative 1 20\% 2 30\% 3 40\% 4 10\% Service times are characterized by a normal distribution with a mean of 10 minutes and a standard deviation of 4 minutes. They are interested in using simulation to find the total amount of service time for each hour of a six-hour working day. They generated the following random numbers for hours 1?6 respectively: 63, 13, 67, 50, 71, and 25. a. On a scale of 00?99, what random number range corresponds to 3 clients arriving per hour? b. What is the number of clients arriving in hour 4? c. What is the total service time in minutes for hour 1?

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a.  Clents Arring  Random Number  per how Categary 10019220493508949099\begin{array} { c c } \text { Clents Arring } & \text { Random Number } \\ \underline { \text { per how} } & \underline { \text { Categary }} \\1 & 00 - 19 \\2 & 20 - 49 \\3 & 50 - 89 \\4 & 90 - 99\end{array}
b.  Hour  Random  Number of  of day Number  Clients Arriving 163321313673450357136252\begin{array}{ccc}\text { Hour } & \text { Random } & \text { Number of } \\\underline{\text { of day} } & \underline{\text { Number } }& \underline{\text { Clients Arriving } }\\1 & 63 & 3 \\2 & 13 & 1 \\3 & 67 & 3 \\4 & 50 & 3 \\5 & 71 & 3 \\6 & 25 & 2\end{array}
c.Hour 1
Client 1: t = 10 + 1.214) = 14.84
Client 2: t = 10 + -1.314) = 4.76
Client 3: t = 10 + -1.124) = 5.52
Total: hour 1 = 25.12 minutes

Hour 2
Client 1: t = 10 + 1.324) = 15.28
Total: hour 2 = 15.28 minutes

Hour 3
Client 1: t = 10 + .864) = 13.44
Client 2: t = 10 + .314) = 11.24
Client 3: t = 10 + -.774) = 6.92
Total: hour 3 = 31.60 minutes

Hour 4
Client 1: t = 10 + 1.904) = 17.60
Client 2: t = 10 + .404) = 11.60
Client 3: t = 10 + -.114) = 9.56
Total: hour 4 = 38.76 minutes

Hour 5
Client 1: t = 10 + -1.634) = 3.48
Client 2: t = 10 + -.754) = 7.00
Client 3: t = 10 + .924) = 13.68
Total: hour 5 = 24.16 minutes

Hour 6
Client 1: t = 10 + -.814) = 6.76
Client 2: t = 10 + -1.124) = 5.52
Total: hour 6 = 12.28 minutes

The Rose Warehouse buys roses each week from Panama. A toll?free long distance call is made on Saturday night, and early Monday morning roses arrive at the airport in a box refrigerated with dry ice. The roses cost $8 a dozen and are sold on a cash-and-carry basis for $28 a dozen. Roses left over at the end of the week are put in a trash collector in an alley behind the store. Past sales rounded to the nearest ten dozen) are as follows: Dozens of Roses Relative 110 5 120 20 130 25 140 30 150 20 The owner of the Rose Warehouse wants to compare two ordering rules for ordering roses: 1) order last week's demand plus 10 dozen extra as (safety stock), (2) order 130 dozen every week. He wants to run an eight-week simulation to compare the average weekly profit for the two rules. Last week's demand was for 110 dozen. He generated the following random numbers for weeks 1?8, respectively: 63, 13, 67, 50, 71, 25, 44, and 00. a. What is the random number range corresponding to 130 dozen roses demanded? b. Using ordering rule 1, what is the profit for week 3? c. Using ordering rule 2, what is the profit for week 6? d. What is the average profit over all eight weeks for ordering rule 1?

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a.  Dozens of Roses  Random Number  Demanded  Category 11000041200524130254914050791508099\begin{array}{cc}\text { Dozens of Roses } & \text { Random Number } \\\underline{\text { Demanded }} & \underline{\text { Category }}\\110 & 00-04 \\120 & 05-24 \\130 & 25-49 \\140 & 50-79 \\150 & 80-99\end{array}

b. If ordered - demand, then profits = ordered)$28 - $8)
If ordered > demand, then profits = demand)$20 - ordered - demand)$8
 Random  Week  Number Demand 163140213120367140450140571140625130744130800110 Rule 1 Ordered Profit 120$24001502160130260015027201502720150244014025201401960 Rule 2 Ordered Profit 130$26001302320130260013026001302600130260013026001302040\begin{array}{c}\begin{array}{ccc|}&\text { Random }\\\underline{ \text { Week }} &\underline{ \text { Number} } & \underline{\text { Demand }} \\ 1 & 63 & 140 \\2 & 13 & 120 \\3 & 67 & 140 \\ 4 & 50 & 140 \\ 5 & 71 & 140 \\6 & 25 & 130 \\ 7 & 44 & 130 \\8 & 00 & 110 \\\end{array}\begin{array}{cc|}\underline{\text { Rule } 1}\\\underline{ \text { Ordered }}&\underline{ \text {Profit }}\\120 & \$ 2400 \\150 & 2160 \\130 & 2600 \\150 & 2720 \\150 & 2720 \\150 & 2440 \\140 & 2520 \\140 & 1960\end{array}\begin{array}{cc}\underline{\text { Rule } 2}\\\underline{ \text { Ordered }}&\underline{ \text {Profit }}\\130 & \$ 2600 \\130 & 2320 \\130 & 2600 \\130 & 2600 \\130 & 2600 \\130 & 2600 \\130 & 2600 \\130 & 2040\end{array}\end{array}

c. $2600
d. Average profit/week = Rule 1: $2440; Rule 2: $2495

There is no single test to prove that a model is 100% valid.

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Which of the following is not correct regarding next-event simulation models?

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Larry sells sweatshirts at football games. The quantity supplied to him is sometimes less than he ordered. The probability distribution below shows the probability of these shortages. 0 0.5 100 0.3 200 0.2 Simulate the average number of shortages for 15 consecutive orders, using the following single digit random numbers: 1, 6, 8, 3, 4, 5, 7, 0, 3, 8, 9, 3, 2, 4, 2.

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The table below shows the frequency of service times for a drive-through window. 1 2 2 6 3 8 4 13 5 13 6 7 7 1 a. If the first category service time of (1 minute) started with random number 00, determine the random numbers for a service time for Category 5, five minutes. b. Determine the random numbers for a service time of seven minutes if the first category starts at random number 00.

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Given the table below with information on lead-time, followed by a set of six random numbers, determine the average lead-time. 3 20\% 4 70\% 5 10\% RANDOM NUMBERS: 90, 52, 54, 47, 56, 95

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The queuing model operating characteristics formula only characterizes short-term average results and, in many practical situations, managers are interested in understanding long-term dynamic behaviors of queuing systems

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A busy municipal golf driving range prepares 300 hotdogs daily. For a variety of reasons, the daily demand for hotdogs varies as follows: 150 0.15 200 0.20 250 0.60 300 0.05 a. If the hotdogs sell for $1.50 each and cost $0.80 each, determine the range's profit or loss on hotdogs for day three using the following random numbers: 00, 59, 02, 97, 69, 98, 93, 49, 51, 92. b. If the hotdogs sell for $1.50 each and cost $0.80 each, determine the range's profit or loss on hotdogs for day eight using the following random numbers: 00, 59, 02, 97, 69, 98, 93, 49, 51, 92. c. If the hotdogs sell for $1.50 each and cost $0.80 each, determine the average daily demand for hotdogs using the following random numbers: 00, 59, 02, 97, 69, 98, 93, 49, 51, 92.

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The Excel function (RAND ) generates random numbers that provide a continuous range of values. Unlike those for two-digit numbers, these values are not limited to probability increments of 0.01.

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Validation consists of all of the following except

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Under what situation would an analytical queuing model be used? When would a simulation model be used?

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All of the following are verification techniques except

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'Balking' means a customer finds the wait while in line too long and thus leaves the line.

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A pastry store wants to know how many dozen muffins to bake each day. Every dozen they sell fresh in the shop returns a profit of $5.00. Every dozen they bake but do not sell on the day they are baked is given to a local charity at a loss of $3.00 a dozen. The business is fairly stable in that they never sell less than 50 dozen nor more than 80 dozen muffins. Their sales history, rounded to the nearest ten dozen muffins is as shown: Dozens of Number of Days 50 12 60 37 70 45 80 18 They want to run a ten day simulation for production rates of 50, 60, 70, and 80 muffins to determine the profit loss) for each. They generated the following random numbers for days 1?10 respectively: 63, 13, 67, 50, 71, 25, 44, 00, 56, and 68. a. What range of random numbers corresponds to 70 muffins sold? b. What is the profit for day 3 if they make 70 dozen muffins? c. What is the average daily profit for all ten days) corresponding to 60 dozen muffins made?

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'Face validity' means the programmers agree to the model's logic.

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In regard to a simulation model for inventory management, all of the following are correct except

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With a fixed-time-increment simulation model, detailed information is lost.

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If variability of demand were the only source of uncertainty, the order quantity and reorder-point decision could be based on a single-period inventory model.

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