Corporation retains a service crew to repair machine breakdowns that occur on an average of 3 per day (approximately Poisson in nature). The crew can service an average of 8 machines per day‚ with a repair time distribution that resembles the exponential distribution. a. What is the utilization rate for this service? b. What is the average downtime for a machine that is broken? c. How many machines are waiting to be serviced at any given time? d. What is the probability that more than one
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30% 46% 16% -.82 3.75 -4.57 Five week moving average 10.73 15.57 7.9 28% 40% 16% 11.17 5.17 -2.72 Five week exponential smoothing 11.58 18.09 8.57 29% 43% 18% 0.62 1.93 -0.59 Three week exponential smoothing 11.13 17.78 7.89 29% 45% 17% -.27 1.74 -2.66 Aggregate demand model 30.57 14% 0.93 Question 2 Next consider using a simple exponential smoothing model. In your analysis‚ test two alpha values‚ .2 and .4. Use the same criteria for evaluating the model
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Calculate the weighted 3-month moving average using weights of 0.50‚ 0.30‚ and 0.20 for periods 4-6. (5 points) c. Calculate the exponential smoothing forecast for periods 2-6 using an initial forecast (F1) 62‚ and an of 0.30. (10 points) d. Calculate the double exponential smoothing forecast for periods 2-6 using an initial trend forecast (T1) of 2.0‚ and initial exponential smoothing forecast (S1) of 60 an of
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following policy: if a customer has to wait‚ the price is $3.50 per gallon; if they don’t have to wait‚ the price is $4.00 per gallon. Customers arrive according to a Poisson process with a mean rate of 20 per hour. Service times at the pump have an exponential distribution with a mean of 2 minutes. Arriving customers always wait until they can by gasoline. Determine the expected price of gasoline per gallon. Problem 3 The Old Colony theme park has a new ride‚ the Double-Disgusting Cyclonic Twister
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A Review of The Limits to Growth The Limits to Growth: a Report for the Club of Rome ’s Project on the Predicament of Mankind was published in 1972 predicting the future of exponential growth of economy and population in a finite world. Since 1972‚ more than 10 million copies in 37 languages have been sold by now (Gambino‚ 2011). This ambitious book is written by MIT researchers for Club of Rome which is an international think tank. The authors created a global computer model‚ Wolrd3‚ to simulate
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Complete the following case study and problems and submit the results in either a Microsoft Word document or a Microsoft Excel spreadsheet. If you choose to use an Excel spreadsheet‚ place each problem on a separate sheet and label the tab with problem number. Save your document with a descriptive file name‚ including the assignment and your name. Chapter 4: North-South Airline Case Study: In January 2008‚ Northern Airlines merged with Southeast Airlines . . . 3-1 Data collected on the yearly demand
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PERENCANAAN & PENGENDALIAN PRODUKSI TIN 4113 Pertemuan 2 • Outline: – – – – – Karakteristik Peramalan Cakupan Peramalan Klasifikasi Peramalan Metode Forecast: Time Series Simple Time Series Models: • Moving Average (Simple & Weighted) • Referensi: – Smith‚ Spencer B.‚ Computer Based Production and Inventory Control‚ Prentice-Hall‚ 1989. – Tersine‚ Richard J.‚ Principles of Inventory and Materials Management‚ Prentice-Hall‚ 1994. – Pujawan‚ Demand Forecasting Lecture Note‚ IE-ITS‚ 2011
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constant service time model) assume‚ or require‚ that the arrival rate can be described by a Poisson distribution and that the service time can be described by a negative exponential distribution. Equivalently‚ we can say that the arrival and service rates must be Poisson‚ and the interarrival time and the service time must be exponential. In practice‚ one would check for this using a statistical Chi Square test: for problems provided here and in the textbook‚ assume that these distributions hold. Note
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What Shapes an Ecosystem? Ecosystems are made up of: * Biotic factors- all living parts of an ecosystem (plants‚ animals‚ bacteria) * Abiotic factors- all nonliving (but natural) parts of an ecosystem (soil‚ wind‚ water) These factors together (biotic and abiotic) determine which types of organisms can live in that particular ecosystem. A habitat- the place where an organism lives- includes both biotic and abiotic factors A niche includes both the habitat of an organism and its unique
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Problem 1: A fast-food franchise is considering opening a drive-up window food service operation. Assume that customer arrivals follow a Poisson distribution‚ with a mean arrival rate of 24 cars per hour‚ and that service times follow an exponential probability distribution. Arriving customers place orders at an intercom station at the back of the parking lot and then drive up to the service window to pay for and receive their order. Compute the following operating characteristics for each
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