The solution to the mean-variance optimization problem using estimated r ̄ is not optimal w.r.t. the solution using the true r ̄.
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The solution to the mean-variance optimization problem using estimated r ̄ is not optimal w.r.t. the solution using the true r ̄.
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- The Tinkan Company produces one-pound cans for the Canadian salmon industry. Each year the salmon spawn during a 24-hour period and must be canned immediately. Tinkan has the following agreement with the salmon industry. The company can deliver as many cans as it chooses. Then the salmon are caught. For each can by which Tinkan falls short of the salmon industrys needs, the company pays the industry a 2 penalty. Cans cost Tinkan 1 to produce and are sold by Tinkan for 2 per can. If any cans are left over, they are returned to Tinkan and the company reimburses the industry 2 for each extra can. These extra cans are put in storage for next year. Each year a can is held in storage, a carrying cost equal to 20% of the cans production cost is incurred. It is well known that the number of salmon harvested during a year is strongly related to the number of salmon harvested the previous year. In fact, using past data, Tinkan estimates that the harvest size in year t, Ht (measured in the number of cans required), is related to the harvest size in the previous year, Ht1, by the equation Ht = Ht1et where et is normally distributed with mean 1.02 and standard deviation 0.10. Tinkan plans to use the following production strategy. For some value of x, it produces enough cans at the beginning of year t to bring its inventory up to x+Ht, where Ht is the predicted harvest size in year t. Then it delivers these cans to the salmon industry. For example, if it uses x = 100,000, the predicted harvest size is 500,000 cans, and 80,000 cans are already in inventory, then Tinkan produces and delivers 520,000 cans. Given that the harvest size for the previous year was 550,000 cans, use simulation to help Tinkan develop a production strategy that maximizes its expected profit over the next 20 years. Assume that the company begins year 1 with an initial inventory of 300,000 cans.It costs a pharmaceutical company 75,000 to produce a 1000-pound batch of a drug. The average yield from a batch is unknown but the best case is 90% yield (that is, 900 pounds of good drug will be produced), the most likely case is 85% yield, and the worst case is 70% yield. The annual demand for the drug is unknown, with the best case being 20,000 pounds, the most likely case 17,500 pounds, and the worst case 10,000 pounds. The drug sells for 125 per pound and leftover amounts of the drug can be sold for 30 per pound. To maximize annual expected profit, how many batches of the drug should the company produce? You can assume that it will produce the batches only once, before demand for the drug is known.FIND THE OPTIMUM SOLUTION TO X= Y= MAX Z=
- a-) find the initial solution using the Vogel's Approximation Method (VAM). and Find the optimal solution.Long-Life Insurance has developed a linear model that it uses to determine the amount of term life Insurance a family of four should have, based on the current age of the head of the household. The equation is: y=150 -0.10x where y= Insurance needed ($000) x = Current age of head of household b. Use the equation to determine the amount of term life Insurance to recommend for a family of four of the head of the household is 40 years old. (Round your answer to 2 decimal places.) Amount of term life insurance thousandsIn the past, Peter Kelle's tire dealership in Baton Rouge sold an average of 1,000 radials each year. In the past 2 years, 220 and 250, respectively were sold in fall, 360 and 320 in winter, 145 and 175 in spring, and 300 and 230 in summer. With a major expansion planned, Kelle projects sales next year to increase to 1,200 radials. Based on next year's projected sales, the demand for each season is going to be (enter your responses as whole numbers): Season Demand Fall nothing
- What combination of x and y will yield the optimum for this problem? Maximize Z = $3x + $15y Subject to: Multiple Choice x= 0, y=4 x= 0, y=3 x= 0, y=0 x= 2y=0 O x=1,y=25 2x + 4y ≤ 12 5x + 2y ≤ 10Calculating outcomes as equally likely would BEST describe: O a. Maximax criterion O b. Laplace criterion O c. Regret criterion Od. Maximin criterion Determining the average payoff for each alternative and choosing the one with the BEST payoff is the approach called: ea, maximax O b. minimax regret O c. laplace Od maximin MIn the past, Peter Kelle's tire dealership in Baton Rouge sold an average of 1,000 radials each year. In the past 2 years, 200 and 260, respectively were sold in fall, 340 and 300 in winter, 150 and 175 in spring, and 300 and 275 in summer. With a major expansion planned, kelle projects sales next year to increase to 1,200 radials. Based on next year's projected sales, the demand for each season is going to be (enter your responses as whole numbers): Season Fall Demand
- City government has collected the following data on annual sales tax collections and new car registrations: Annual Sales Tax Collections (in millions) 1.0 1.4 1.9 2.0 1.8 2.1 2.3 2.5 New Car Registrations (in millions) 10 12 15 16 14 17 20 22 Determine the following: Plot these data and decide if a linear model is reasonable. Using the results of part a., find the estimated sales tax collections if new car registrations total 25,000,000.Elaborate/ Explain Integer Linear Optimization and put examples2 Vidhya Balan is planning to liquidate her investments in mutual funds and invest in real estate. Before making the change to her investment strategy, Vidhya wants to forecast the price of mutual funds for the next 2 months. She has collected the following data on the average fund prices for the past 10 months. Average Month Fund Price 1. 55.1 53.8 3 53.4 4 52.95 5 52.15 6. 52.75 7 52.65 8 51.5 9. 52.25 10 51.7 Using a five-period moving average, forecast the a average fund price for Period 11. b. |Using exponential smoothing with a = 0.3 forecast the average fund price for Period 11. Assume an initial forecast for Month 2 (F2) as 55.10