1) Modify PC Tech's product mix model so that there is no maximum sales constraint. Does this make the problem unbounded? Does it change the optimal solution at all?
Explain its effect.
2) Use SolverTable to run a sensitivity analysis on the cost per assembling labor hours, letting it vary from $5 to $20 in increment of $1. Keep track of the computers produced in row 21, the hours used in the range B26:B28, and the total profit. Discuss your findings. Are they intuitively what you expected?
3) Modify the Pigskin spreadsheet model so that except for month 6, demand need not be met on time. The only requirement is that all demand be met eventually by the end of month 6. How does this change the optimal production schedule? How does it change the optimal total cost?
4) Extra Credit. A furniture company manufactures desks and chairs. Each desk uses four units of wood, and each chair uses three units of wood. A desk contributes $400 to profit, and a chair contributes $250. Marketing restrictions require that the number of chairs produced be at least twice the number of desks produced. There are 2000 units of wood available.
a. Develop a linear program for this product mix problem.
b. Use Solver to maximize the company's profit.
c. Confirm graphically that the solution is part (a) maximizes the company's profit.
d. Report Solver Sensitivity reports and analyze the results.
e. Use SolverTable to see what happens to the decision variables and the total profit when the availability of wood varies from 1000 to 3000 in 100-unit increments. Based on your findings, how much would the company be willing to pay for each extra unit of wood over its current 2000 units? How much profit would the company lose if it lost any of its current 2000 units?