Please solve it as soon as possible York Appliance Company (YAC) makes pizza ovens for commercial use. Jack Wood, the CEO, iscontemplating a new project which produces smaller ovens for use in high school and collegekitchens. The activities necessary to build an experimental model (Model: YAC-03) and related dataare given in the following table.ImmediatePredecessorsNormalTimeCrashTimeNormalCrashActivityCost ($)Cost ($)(Weeks)(Weeks)ANone42,0502,325BNone12,2002,800CA35005002,7001,8503,500D842,300EА, В1,550F323,000GС, Е41,4002,200HG8001,0001,5002,200D, G431,650JH, I42,950a) Construct a network diagram and determine ES, EF, LS and LF for each activity.b) Find slack times of all activities.c) Determine the expected completion time and critical path/s.d) If Jack wishes to reduce the time required to complete this project by four weeks, please help himfill out the following table completely.Completion Timebefore CrashingActivity/ies tobe CrashedTrial #Critical PathsCrash Coste) How much does it cost to crash the project by four weeks, and how much will it cost to completethe crashed project?

As per Bartleby guidelines, we can only solve the first three subparts of one question at a…

Answered: truct a network diagram and determine…

truct a network diagram and determine ES, EF slack times of all activities. mine the expected completion time and critica k wishes to reduce the time required to compl uired

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.4: Multiple Regression Models

Problem 15P: Stock market analysts are continually looking for reliable predictors of stock prices. Consider the...

See similar textbooks

Similar questions

An automobile manufacturer is considering whether to introduce a new model called the Racer. The profitability of the Racer depends on the following factors: The fixed cost of developing the Racer is triangularly distributed with parameters 3, 4, and 5, all in billions. Year 1 sales are normally distributed with mean 200,000 and standard deviation 50,000. Year 2 sales are normally distributed with mean equal to actual year 1 sales and standard deviation 50,000. Year 3 sales are normally distributed with mean equal to actual year 2 sales and standard deviation 50,000. The selling price in year 1 is 25,000. The year 2 selling price will be 1.05[year 1 price + 50 (% diff1)] where % diff1 is the number of percentage points by which actual year 1 sales differ from expected year 1 sales. The 1.05 factor accounts for inflation. For example, if the year 1 sales figure is 180,000, which is 10 percentage points below the expected year 1 sales, then the year 2 price will be 1.05[25,000 + 50( 10)] = 25,725. Similarly, the year 3 price will be 1.05[year 2 price + 50(% diff2)] where % diff2 is the percentage by which actual year 2 sales differ from expected year 2 sales. The variable cost in year 1 is triangularly distributed with parameters 10,000, 12,000, and 15,000, and it is assumed to increase by 5% each year. Your goal is to estimate the NPV of the new car during its first three years. Assume that the company is able to produce exactly as many cars as it can sell. Also, assume that cash flows are discounted at 10%. Simulate 1000 trials to estimate the mean and standard deviation of the NPV for the first three years of sales. Also, determine an interval such that you are 95% certain that the NPV of the Racer during its first three years of operation will be within this interval.
Stock market analysts are continually looking for reliable predictors of stock prices. Consider the problem of modeling the price per share of electric utility stocks (Y). Two variables thought to influence this stock price are return on average equity (X1) and annual dividend rate (X2). The stock price, returns on equity, and dividend rates on a randomly selected day for 16 electric utility stocks are provided in the file P13_15.xlsx. Estimate a multiple regression equation using the given data. Interpret each of the estimated regression coefficients. Also, interpret the standard error of estimate and the R-square value for these data.
Play Things is developing a new Lady Gaga doll. The company has made the following assumptions: The doll will sell for a random number of years from 1 to 10. Each of these 10 possibilities is equally likely. At the beginning of year 1, the potential market for the doll is two million. The potential market grows by an average of 4% per year. The company is 95% sure that the growth in the potential market during any year will be between 2.5% and 5.5%. It uses a normal distribution to model this. The company believes its share of the potential market during year 1 will be at worst 30%, most likely 50%, and at best 60%. It uses a triangular distribution to model this. The variable cost of producing a doll during year 1 has a triangular distribution with parameters 15, 17, and 20. The current selling price is 45. Each year, the variable cost of producing the doll will increase by an amount that is triangularly distributed with parameters 2.5%, 3%, and 3.5%. You can assume that once this change is generated, it will be the same for each year. You can also assume that the company will change its selling price by the same percentage each year. The fixed cost of developing the doll (which is incurred right away, at time 0) has a triangular distribution with parameters 5 million, 7.5 million, and 12 million. Right now there is one competitor in the market. During each year that begins with four or fewer competitors, there is a 25% chance that a new competitor will enter the market. Year t sales (for t 1) are determined as follows. Suppose that at the end of year t 1, n competitors are present (including Play Things). Then during year t, a fraction 0.9 0.1n of the company's loyal customers (last year's purchasers) will buy a doll from Play Things this year, and a fraction 0.2 0.04n of customers currently in the market ho did not purchase a doll last year will purchase a doll from Play Things this year. Adding these two provides the mean sales for this year. Then the actual sales this year is normally distributed with this mean and standard deviation equal to 7.5% of the mean. a. Use @RISK to estimate the expected NPV of this project. b. Use the percentiles in @ RISKs output to find an interval such that you are 95% certain that the companys actual NPV will be within this interval.
A company manufacturers a product in the United States and sells it in England. The unit cost of manufacturing is 50. The current exchange rate (dollars per pound) is 1.221. The demand function, which indicates how many units the company can sell in England as a function of price (in pounds) is of the power type, with constant 27556759 and exponent 2.4. a. Develop a model for the companys profit (in dollars) as a function of the price it charges (in pounds). Then use a data table to find the profit-maximizing price to the nearest pound. b. If the exchange rate varies from its current value, does the profit-maximizing price increase or decrease? Does the maximum profit increase or decrease?
Based on Babich (1992). Suppose that each week each of 300 families buys a gallon of orange juice from company A, B, or C. Let pA denote the probability that a gallon produced by company A is of unsatisfactory quality, and define pB and pC similarly for companies B and C. If the last gallon of juice purchased by a family is satisfactory, the next week they will purchase a gallon of juice from the same company. If the last gallon of juice purchased by a family is not satisfactory, the family will purchase a gallon from a competitor. Consider a week in which A families have purchased juice A, B families have purchased juice B, and C families have purchased juice C. Assume that families that switch brands during a period are allocated to the remaining brands in a manner that is proportional to the current market shares of the other brands. For example, if a customer switches from brand A, there is probability B/(B + C) that he will switch to brand B and probability C/(B + C) that he will switch to brand C. Suppose that the market is currently divided equally: 10,000 families for each of the three brands. a. After a year, what will the market share for each firm be? Assume pA = 0.10, pB = 0.15, and pC = 0.20. (Hint: You will need to use the RISKBINOMLAL function to see how many people switch from A and then use the RISKBENOMIAL function again to see how many switch from A to B and from A to C. However, if your model requires more RISKBINOMIAL functions than the number allowed in the academic version of @RISK, remember that you can instead use the BENOM.INV (or the old CRITBENOM) function to generate binomially distributed random numbers. This takes the form =BINOM.INV (ntrials, psuccess, RAND()).) b. Suppose a 1% increase in market share is worth 10,000 per week to company A. Company A believes that for a cost of 1 million per year it can cut the percentage of unsatisfactory juice cartons in half. Is this worthwhile? (Use the same values of pA, pB, and pC as in part a.)
Suppose that a regional express delivery service company wants to estimate the cost of shipping a package (Y) as a function of cargo type, where cargo type includes the following possibilities: fragile, semifragile, and durable. Costs for 15 randomly chosen packages of approximately the same weight and same distance shipped, but of different cargo types, are provided in the file P13_16.xlsx. a. Estimate a regression equation using the given sample data, and interpret the estimated regression coefficients. b. According to the estimated regression equation, which cargo type is the most costly to ship? Which cargo type is the least costly to ship? c. How well does the estimated equation fit the given sample data? How might the fit be improved? d. Given the estimated regression equation, predict the cost of shipping a package with semifragile cargo.
If a monopolist produces q units, she can charge 400 4q dollars per unit. The variable cost is 60 per unit. a. How can the monopolist maximize her profit? b. If the monopolist must pay a sales tax of 5% of the selling price per unit, will she increase or decrease production (relative to the situation with no sales tax)? c. Continuing part b, use SolverTable to see how a change in the sales tax affects the optimal solution. Let the sales tax vary from 0% to 8% in increments of 0.5%.
Carlisle Tire and Rubber, Inc., is considering expanding production to meet potential increases in the demand for one of its tire products. Carlisle’s alternatives are to construct a new plant, expand the existing plant, or do nothing in the short run. The market for this particular tire product may expand, remain stable, or contract. Carlisle’s marketing department estimates the probabilities of these market outcomes to be 0.25, 0.35, and 0.40, respectively. The file P09_31.xlsx contains Carlisle’s payoffs and costs for the various combinations of decisions and outcomes. a. Use PrecisionTree to identify the strategy that maximizes this tire manufacturer’s expected profit. b. Perform a sensitivity analysis on the optimal decision, letting each of the monetary inputs vary one at a time plus or minus 10% from its base value, and summarize your findings. Which of the inputs appears to have the largest effect on the best solution? Tire plant decisions Decision\outcome…
#28Even though independent gasoline stations have been having a difficult time, Susan Solomon hasbeen thinking about starting her own independent gasoline station. Susan’s problem is to decide howlarge her station should be. The annual returns will depend on both the size of her station and a numberof marketing factors related to the oil industry and demand for gasoline. After a careful analysis, Susandeveloped the following table: GOOD FAIR POORSIZE OF MARKET MARKET MARKETFIRST STATION ($) ($) ($)Small 50,000 20,000 –10,000Medium 80,000 30,000 –20,000Large 100,000 30,000 –40,000Very large 300,000 25,000 –160,000For example, if Susan constructs a…
Highline Financial Services provides three categories of service toits clients. Managing partner Freddie Mack is getting ready to preparefinancial and personnel hiring (or layoff) plans for the comingyear. He is a bit perplexed by the following printout he obtained,which seems to show oscillating demand for the three categoriesof services over the past eight quarters:Examine the demand that this company has experienced for thethree categories of service it offers over the preceding two years.Assuming nothing changes in terms of advertising or promotion,and competition doesn’t change, predict demand for the servicesthe company offers for the next four quarters. Note that there arenot enough data to develop seasonal relatives. Nonetheless, youshould be able to make reasonably good, approximate intuitiveestimates of demand. What general observations can you makeregarding demand? Should Freddie have any concerns? Explain.
(Business Analytics) Problem 1) Maureen Laird is the chief financial officer for the Alva Electric Co., a major public utility in the Midwest. The company has scheduled the construction of new hydroelectric plants 5, 10, and 20 years from now to meet the needs ofthe growing population in the region served by the company. To cover the construction costs, Maureen needs to invest some of the company’s money now to meet these future cash flow needs. Maureen may purchase only three kinds of financial assets, each of which costs $1 million per unit. Fractional units may be purchased. The assets produce income 5, 10, and 20 years from now, and that income is needed to cover minimum cash flow requirements in those years, as shown in the following table. Income Per Unit of Assets Year Asset 1 Asset 2 Asset 3 Minimum Cash Flow Required 5 $8 Million $2 Million $2 Million $1.6 Billion 10 $2 Million $4 Million $4 Million $400…
The table below shows the sales figures for a brand of shoe over the last 12 months.Months SalesJanuary 69February 75March 86April 92May 95June 100July 108August 115September 125October 131November 140December 150a. Using the following, forecast the sales for the months up to January the following year:-i. A simple three month moving average. ii. A three period weighted moving average using weights of 1, 2 and 3. Assign the highest weight to the most recent data. iii. Exponential Smoothing when α= .6 and the forecast for March is 350.iv. Determine which of the three forecasting technique is the most accurate using MAD.