A bakery must decide how many pies to prepare for the upcomi…

A bakery must decide how many pies to prepare for the upcoming weekend. The bakery has the option to make 50, 100, or 150 pies.  Assume that demand for the pies can be 50, 100, or 150.  Each pie costs $5 to make and sells for $7.  Unsold pies are donated to a nearby charity center.  Assume that there is no opportunity cost for lost sales. Which alternative should be chosen based on the minimax regret criterion?     States of nature   50 100 150 50       100       150      

Study Ledge employees part time workers who combine to work…

Study Ledge employees part time workers who combine to work a total of 10 hours per day producing study packets. The labor cost for these worked is $8 per hour.  Last semester, the workers combined to produce 650 study packets per work day. This semester they have leased a faster printer which is estimated to cost an additional $20/hour when being used to print packages and is expected to increase labor productivity by 40%. What is the new labor productivity expected to be?

Sterling Archer runs a tie factory. The factory makes 4 type…

Sterling Archer runs a tie factory. The factory makes 4 types of ties, Silk, Polyester, Blend 1 and Blend 2.  Blend 1 and Blend 2 each are cotton polyester blends.  Archer is limited each week in the number he can make by the amount of each of the three raw materials he can order from his vendor.  He also has maximum demands on each tie type as well as contractually obligated minimums that he must produce.  He has optimized his production strategy to maximize profit using a linear program.  The sensitivity analysis is below.  How much more money could Mr. Archer make each week, according to the model, if he could get is vender to sell him 10% more cotton than he currently receives at his current price?       Final Reduced Objective Allowable Allowable Cell Name Value Cost Coefficient Increase Decrease $B$3 Number of Units Silk 7000 0 3.45 1E+30 3.45 $C$3 Number of Units Poly 13625 0 2.32 2.176 0.952 $D$3 Number of Units Blend 1 13100 0 2.81 0.34 1.36 $E$3 Number of Units Blend 2 8500 0 3.25 1E+30 0.476     Final Shadow Constraint Allowable Allowable Cell Name Value Price R.H. Side Increase Decrease $F$11 Yards of Silk 875 0 1000 1E+30 125 $F$12 Yards of Poly 2000 29 2000 30 290 $F$13 Yards of Cotton 1250 27.2 1250 145 5 $F$14 Max Silk 7000 3.45 7000 1000 1000 $F$15 Max Poly 13625 0 14000 1E+30 375 $F$16 Max B1 13100 0 16000 1E+30 2900 $F$17 Max B2 8500 0.476 8500 71.42857143 2071.428571 $F$18 Min Silk 7000 0 6000 1000 1E+30 $F$19 Min Poly 13625 0 10000 3625 1E+30 $F$20 Min B1 13100 0 13000 100 1E+30 $F$21 Min B2 8500 0 6000 2500 1E+30

Carla’s Cupcakes must decide how many cupcakes to order so a…

Carla’s Cupcakes must decide how many cupcakes to order so as to best meet demand without having too many cupcakes go unsold. The history of sales is given below. Calculate the forecasted demand for May using exponential smoothing with trend adjustment. The forecast for January was 65 and the initial trend estimate was 0. Smoothing constants alpha = 0.2 and beta = 0.3. (choose the nearest answer) Month Sales January 80 February 105 March 125 April 140

Jim’s department at a local department store has tracked the…

Jim’s department at a local department store has tracked the sales of a product over the last ten weeks. Forecast demand using exponential smoothing with an alpha of 0.4, and an initial forecast of 18.0 for period 1. Calculate the MAD and use it to calculate the tracking signal for the entire forecast from period 1 through period 10.  Answer to two decimal places. Period Demand 1 14 2 13 3 16 4 18 5 17 6 21 7 23 8 25 9 25 10 28

The quarterly sales for specific educational software over t…

The quarterly sales for specific educational software over the past three years are given in the following table. Compute the seasonal index for Quarter 4. (choose the nearest answer)   YEAR 1 YEAR 2 YEAR 3 Quarter 1 1710 1820 1830 Quarter 2 960 910 1090 Quarter 3 2720 2840 2900 Quarter 4 2430 2200 2590  

The operations manager for a local bus company wants to deci…

The operations manager for a local bus company wants to decide whether he should purchase a small, medium, or large new bus for his company. He estimates that the annual profits (in $000) will vary depending upon whether passenger demand is low, moderate, or high, as follows: Bus             Low Demand     Medium Demand         High Demand      Small 50 60 70 Medium 40 80 90 Large 20 50 120 If he feels the chances of low, moderate, and high demand are 30%, 30%, and 40% respectively, what is his expected value of perfect information?