Based on the following sensitivity analysis, which of the following products would be considered most sensitive to changes or errors in the objective function coefficient? Variable Cells Final Objective Coefficient Allowable Allowable Cell Reduced Cost I -2 Name Value Increase Decrease $B$2 $B$3 $B$4 Product 1 25 10 Product 2 175 25 10 Product 3 -1.5 25 12 3 Constraints Final Shadow Constraint Allowable Allowable Cell Name Value Price R.H.Side Increase Decrease SH$9 ResourceA 100 1E+30 100 $H$10 ResourceB 525 800 1E+30 275 $H$11 ResourceC 700 1.75 366.6666667 700 700 O Product_2 O Product_1 O Product_3
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- Suppose you have invested 25% of your portfolio in four different stocks. The mean and standard deviation of the annual return on each stock are shown in the file P11_46.xlsx. The correlations between the annual returns on the four stocks are also shown in this file. a. What is the probability that your portfolios annual return will exceed 30%? b. What is the probability that your portfolio will lose money during the year?The method for rating teams in Example 7.8 is based on actual and predicted point spreads. This method can be biased if some teams run up the score in a few games. An alternative possibility is to base the ratings only on wins and losses. For each game, you observe whether the home team wins. Then from the proposed ratings, you predict whether the home team will win. (You predict the home team will win if the home team advantage plus the home teams rating is greater than the visitor teams rating.) You want the ratings such that the number of predictions that match the actual outcomes is maximized. Try modeling this. Do you run into difficulties? (Remember that Solver doesnt like IF functions.) EXAMPLE 7.8 RATING NFL TEAMS9 We obtained the results of the 256 regular-season NFL games from the 2015 season (the 2016 season was still ongoing as we wrote this) and entered the data into a spreadsheet, shown at the bottom of Figure 7.38. See the file NFL Ratings Finished.xlsx. (Some of these results are hidden in Figure 7.38 to conserve space.) The teams are indexed 1 to 32, as shown at the top of the sheet. For example, team 1 is Arizona, team 2 is Atlanta, and so on. The first game entered (row 6) is team 19 New England versus team 25 Pittsburgh, played at New England. New England won the game by a score of 28 to 21, and the point spread (home team score minus visitor team score) is calculated in column J. A positive point spread in column J means that the home team won; a negative point spread indicates that the visiting team won. The goal is to determine a set of ratings for the 32 NFL teams that most accurately predicts the actual outcomes of the games played.Suppose that GLC earns a 2000 profit each time a person buys a car. We want to determine how the expected profit earned from a customer depends on the quality of GLCs cars. We assume a typical customer will purchase 10 cars during her lifetime. She will purchase a car now (year 1) and then purchase a car every five yearsduring year 6, year 11, and so on. For simplicity, we assume that Hundo is GLCs only competitor. We also assume that if the consumer is satisfied with the car she purchases, she will buy her next car from the same company, but if she is not satisfied, she will buy her next car from the other company. Hundo produces cars that satisfy 80% of its customers. Currently, GLC produces cars that also satisfy 80% of its customers. Consider a customer whose first car is a GLC car. If profits are discounted at 10% annually, use simulation to estimate the value of this customer to GLC. Also estimate the value of a customer to GLC if it can raise its customer satisfaction rating to 85%, to 90%, or to 95%. You can interpret the satisfaction value as the probability that a customer will not switch companies.
- A company that supplies gasoline to a city has recorded the weeklyusage (tons/week) for the past 3 years. The file BA3653GasolineRecord.xlsxcontains this record. (c) In general, the company delivers the demanded gasoline to customersthat store it in their own facilities. However, the company would like toobtain its own storage tanks to better handle variability. The companyhas identified several solutions: a 500 ton, a 1000 ton, a 2000 ton and a3000 ton system, with each tank being proportionately more expensiveas its size grows. Given your predictions and the expected variability,what size of tank would you choose?(d) Reaching the city is sometimes hazardous due to weather conditions.Even with these challenges, the company estimates that the most thatshipments to the city may be delayed is 1 week. Given this information,which tank choice (of those in part c) do you think would be appropriate? week demand (tons) 1 1174.5 2 1316.2 3 1197 4 1127.3 5 1193.1 6 1260.7 7…In 2020, a manufacturing company instituted a total quality management (TQM) program producingthe comparative report shown below:[LO 17-5]Summary COQ Report(in thousands)2019 2020 % ChangePrevention costs $ 200 $ 300 +50Appraisal costs 210 315 +50Internal failure costs 190 114 −40External failure costs 1,200 621 −48Total COQ $1,800 $1,350 −25On the basis of this report, which one of the following statements is most likely correct?a. An increase in conformance costs resulted in a higher-quality product and, therefore, a decreasein nonconformance costs.b. An increase in inspection costs was solely responsible for the decrease in quality costs.c. Quality costs such as scrap and rework decreased by 48%.d. Quality costs such as returns and repairs under warranty decreased by 40%.e. Nonconformance costs increased by 50% and conformance costs decreased by approximately 47%.Hi is this correct?The management of an oil company is trying to decide whether to drill for oil in a particular fieldin the Gulf of Mexico. It costs the company $600 thousand to drill in the selected field. Themanagement believes that if oil is found in this field, its estimated value will be $3400 thousand. Atpresent, this oil company believes that there is a 45% chance that the selected field actually containsoil. Before drilling, the oil company can hire a team of geologists to perform seismographic tests at acost of $55 thousand. Based on similar tests in other fields, the tests have a 25% false negative rate(no oil predicted when oil is present) and a 15% false positive rate (oil predicted when no oil ispresent).A. Assume the oil company wants to maximize its expected net earnings. Please utilize decisiontree analysis to determine its optimal strategy.B. Calculate the expected value of the information (EVI/EVSI) provided by the team ofgeologists.C. Calculate and interpret EVPI…
- 4. What is the optimized Z value for this following LP problem? Minimize Z= 3x + 10y, subject to (1) 2x + 4y ≤ 12 and (2) 5x + 2y ≥ 10 and (3) x, y ≥ 0. Answer: ______________The LP relationships that follow were formulated by Richard Martin at the Long Beach Chemical Company. Maximize 4X1+12X1X2+5X3 Subject to: 2X1X2+2X3≤70 (C1) 10.9X1−4X2≥15.6 (C2) 10X1+3X2+3X3≥21 (C3) 16X2−13X3=17 (C4) −4X1−X2+4X3=5 (C5) 7X1+2X2+3X3≤80 (C6) For an LP, the objective function developed by Richard is (valid or onvalid) . Constraint C1 is a(n) (valid or onvalid) LP constraint. Constraint C2 is a(n) (valid or onvalid) LP constraint. Constraint C3 is a(n) (valid or onvalid) LP constraint. Constraint C4 is a(n) (valid or onvalid) LP constraint. Constraint C5 is a(n) (valid or onvalid) LP constraint. Constraint C6 is a(n) (valid or onvalid) LP constraint.2 Vidhya Balan is planning to liquidate her investments inmutual funds and invest in real estate. Before makingthe change to her investment strategy, Vidhya wants toforecast the price of mutual funds for the next 2 months.She has collected the following data on the average fundprices for the past 10 months.Month Average Fund Price1 55.12 53.83 53.44 52.955 52.156 52.757 52.658 51.59 52.2510 51.7a Using a five-period moving average, forecast theaverage fund price for Period 11.b. Using exponential smoothing with α = 0.3 forecastthe average fund price for Period 11. Assume an initialforecast for Month 2 (F2) as 55.10
- Zara stores in the United States stocks a particular type of designer denim jeans in the United States. It stores 500 pairs of jeans each month from its two suppliers. The Hong Kong supplier charges Zara $11 per pair of jeans, and the Colombian supplier charges $16 per pair (and then Zara marks them up almost 1,000%). Although the jeans from Hong Kong are less expensive, they also have more defects than those from Colombia. Based on past data, Zara estimates that 7% of the Hong Kong jeans will be defective compared to only 2% from Colombia and Zara does not want to import any more than 5% defective items. However, Zara does not want to rely on a single supplier, so it wants to order at least 20% from each supplier every month. A. Formulate a linear programming model for this problem. B.Solve the linear programming model graphically. Use either iso-line or corner point method. How many of each should Zara buy? C. How much will Zara pay for them? D. If the Hong Kong supplier were able to…Zara stores in the United States stocks a particular type of designer denim jeans in the United States. It stores 500 pairs of jeans each month from its two suppliers. The Hong Kong supplier charges Zara $11 per pair of jeans, and the Colombian supplier charges $16 per pair (and then Zara marks them up almost 1,000%). Although the jeans from Hong Kong are less expensive, they also have more defects than those from Colombia. Based on past data, Zara estimates that 7% of the Hong Kong jeans will be defective compared to only 2% from Colombia and Zara does not want to import any more than 5% defective items. However, Zara does not want to rely on a single supplier, so it wants to order at least 20% from each supplier every month.a. Formulate a linear programming model for this problem. b. Solve the linear programming model graphically. Use either iso-line or corner point method. How many of each should Zara buy? c. How much will Zara pay for them? solve in excel Speak SpeakBelow you are given a partial computer output from a multiple regression analysis based on a sample of 16 observations. Coefficients Standard Error Constant 12.924 4.425 x1 -3.682 2.630 x2 45.216 12.560 Analysis of Variance Source ofVariation Degrees ofFreedom Sum ofSquares MeanSquare F Regression 4853 2426.5 Error 485.3 The t value obtained from the table which is used to test an individual parameter at the 1% level is a. 2.977. b. 2.921. c. 3.012. d. 2.650.