The University Research Center wants to forecast the number of students who will enroll in the SABH programs (BSAC, BSMA, BSBA, BSTM, BSHM) next semester, in order to determine how many sections to schedule. The registrar has provided the following enrollment data for the past eight semesters: SEMESTER First Semester, SY 2017-2018 Second Semester, SY 2017-2018 Short Term, SY 2017-2018 First Semester, SY 2018-2019 Second Semester, SY 2018-2019 Short Term, SY 2018-2019 First Semester, SY 2019-2020 Second Semester, SY 2019-2020 STUDENTS ENROLLED IN SABH PROGRAMS 400 450 350 420 500 575 490 650 a. Compute a three-semester moving average forecast for school year 2018-2019 onwards. b. Construct a table showing the exponentially smoothed forecast (a = 0.25) for the enrollment data. C. Construct a table showing the adjusted exponentially smoothed forecast using B = 0.3 %3D

The University Research Center wants to forecast the number of students who will enroll in the SABH programs (BSAC, BSMA, BSBA, BSTM, BSHM) next semester, in order to determine how many sections to schedule. The registrar has provided the following enrollment data for the past eight semesters: SEMESTER First Semester, SY 2017-2018 Second Semester, SY 2017-2018 Short Term, SY 2017-2018 First Semester, SY 2018-2019 Second Semester, SY 2018-2019 Short Term, SY 2018-2019 First Semester, SY 2019-2020 Second Semester, SY 2019-2020 STUDENTS ENROLLED IN SABH PROGRAMS 400 450 350 420 500 575 490 650 a. Compute a three-semester moving average forecast for school year 2018-2019 onwards. b. Construct a table showing the exponentially smoothed forecast (a = 0.25) for the enrollment data. C. Construct a table showing the adjusted exponentially smoothed forecast using B = 0.3 %3D

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter11: Simulation Models

Section: Chapter Questions

Problem 69P: The Tinkan Company produces one-pound cans for the Canadian salmon industry. Each year the salmon...

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The Pigskin Company produces footballs. Pigskin must decide how many footballs to produce each month. The company has decided to use a six-month planning horizon. The forecasted monthly demands for the next six months are 10,000, 15,000, 30,000, 35,000, 25,000, and 10,000. Pigskin wants to meet these demands on time, knowing that it currently has 5000 footballs in inventory and that it can use a given months production to help meet the demand for that month. (For simplicity, we assume that production occurs during the month, and demand occurs at the end of the month.) During each month there is enough production capacity to produce up to 30,000 footballs, and there is enough storage capacity to store up to 10,000 footballs at the end of the month, after demand has occurred. The forecasted production costs per football for the next six months are 12.50, 12.55, 12.70, 12.80, 12.85, and 12.95, respectively. The holding cost incurred per football held in inventory at the end of any month is 5% of the production cost for that month. (This cost includes the cost of storage and also the cost of money tied up in inventory.) The selling price for footballs is not considered relevant to the production decision because Pigskin will satisfy all customer demand exactly when it occursat whatever the selling price is. Therefore. Pigskin wants to determine the production schedule that minimizes the total production and holding costs. Can you guess the results of a sensitivity analysis on the initial inventory in the Pigskin model? See if your guess is correct by using SolverTable and allowing the initial inventory to vary from 0 to 10,000 in increments of 1000. Keep track of the values in the decision variable cells and the objective cell.
The Pigskin Company produces footballs. Pigskin must decide how many footballs to produce each month. The company has decided to use a six-month planning horizon. The forecasted monthly demands for the next six months are 10,000, 15,000, 30,000, 35,000, 25,000, and 10,000. Pigskin wants to meet these demands on time, knowing that it currently has 5000 footballs in inventory and that it can use a given months production to help meet the demand for that month. (For simplicity, we assume that production occurs during the month, and demand occurs at the end of the month.) During each month there is enough production capacity to produce up to 30,000 footballs, and there is enough storage capacity to store up to 10,000 footballs at the end of the month, after demand has occurred. The forecasted production costs per football for the next six months are 12.50, 12.55, 12.70, 12.80, 12.85, and 12.95, respectively. The holding cost incurred per football held in inventory at the end of any month is 5% of the production cost for that month. (This cost includes the cost of storage and also the cost of money tied up in inventory.) The selling price for footballs is not considered relevant to the production decision because Pigskin will satisfy all customer demand exactly when it occursat whatever the selling price is. Therefore. Pigskin wants to determine the production schedule that minimizes the total production and holding costs. As indicated by the algebraic formulation of the Pigskin model, there is no real need to calculate inventory on hand after production and constrain it to be greater than or equal to demand. An alternative is to calculate ending inventory directly and constrain it to be nonnegative. Modify the current spreadsheet model to do this. (Delete rows 16 and 17, and calculate ending inventory appropriately. Then add an explicit non-negativity constraint on ending inventory.)
The Pigskin Company produces footballs. Pigskin must decide how many footballs to produce each month. The company has decided to use a six-month planning horizon. The forecasted monthly demands for the next six months are 10,000, 15,000, 30,000, 35,000, 25,000, and 10,000. Pigskin wants to meet these demands on time, knowing that it currently has 5000 footballs in inventory and that it can use a given months production to help meet the demand for that month. (For simplicity, we assume that production occurs during the month, and demand occurs at the end of the month.) During each month there is enough production capacity to produce up to 30,000 footballs, and there is enough storage capacity to store up to 10,000 footballs at the end of the month, after demand has occurred. The forecasted production costs per football for the next six months are 12.50, 12.55, 12.70, 12.80, 12.85, and 12.95, respectively. The holding cost incurred per football held in inventory at the end of any month is 5% of the production cost for that month. (This cost includes the cost of storage and also the cost of money tied up in inventory.) The selling price for footballs is not considered relevant to the production decision because Pigskin will satisfy all customer demand exactly when it occursat whatever the selling price is. Therefore. Pigskin wants to determine the production schedule that minimizes the total production and holding costs. Modify the Pigskin model so that there are eight months in the planning horizon. You can make up reasonable values for any extra required data. Dont forget to modify range names. Then modify the model again so that there are only four months in the planning horizon. Do either of these modifications change the optima] production quantity in month 1?
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KrazySockzThe KrazySockz Company is known for their colorful yetcomfortable socks. They have forecasted their demand for the nextsix months as follows: Month 1 demand is 30,000, month 2demand is 50,000, month 3 demand is 20,000, month 4 demand is10,000, month 5 demand is 15,000 and month 6 demand is 20,000.At the beginning of month 1 they have 15,000 pairs of socks onhand. KrazySockz currently has 40 production employees. Each productionemployee costs the company the company $4,000 per month ($3,200 salary and $800in other costs) per month. Production employees can work up to 160 hours permonth before they must be paid overtime. Overtime is paid at a rate of $30 per hourand production employees can not work more than 30 hours per month overtime. Ittakes 15 minutes of labor and $0.75 of raw material to produce a pair of socks.KrazySockz can hire or fire employees each month. Hiring a production employeeincurs a cost of $3,500 and firing a production employee costs $4,500. At the end…
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Business Analytics department chair will be scheduling faculty to teach courses during thecoming fall semester. Four core courses need to be covered. The four courses are at theUG, MBA, MS, and Ph.D. levels. Four professors will be assigned to the courses, witheach professor receiving one of the courses. Student evaluations of professors are availablefrom previous semesters. Based on a rating scale of 1 to 5, the average student evaluationsfor each professor are shown in the following table. Professor C does not have a Ph.D.and cannot be assigned to teach the Ph.D. level course. If the department chair makesteaching assignments based on maximizing the student evaluation ratings over all fourcourses, what staff assignments should be made?CourseProfessor UG MBA MS Ph.D.A 4.2 4.7 4.3 4.2B 4.1 4.4 3.9 4.5C 4.6 4.1 4.2 -D 4.8 4.0 4.6 4.4a) Develop a network representation of this problem.b) Formulate a linear programming model for this problem.c) Solve the problem by using Excel Solver…
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The following table represents sales data for milk (in hundred liters) sold by a grocery. Do the computations to fill out the table and answer the following questions: Using MAD as the criterion, which of the following models would you use for the given time series data? Why? Naïve approach; 5-month SMA model; WMA model with weights 0.1, 0.3, and 0.6; or ES model with α = 0.5 and a forecast of 3,500 liters in the first month. NOTE: In answering Item 1, mention the whole description of the model; i.e., not just “SMA model”, but “SMA model with n = …”; not just “WMA model”, but “WMA model with weights …”; not just “ES model”, but “ES model with α = …”. Interpret the MAD of the most accurate among the forecasting models above. 3. Based on your decision in Item 1, what should be the forecast for Month 11?
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