Complete question, its mixed in different order

Amanufacturing facility for Company XYZ that produces doors and windows utilizes three manufacturing processes: cutting, sanding and finishing. There are limited resources for each of these processes. Assume that the decision variables are defined to represent the number of doors produced per week and the number of windows produced per week. Assume that the objective function is a profit maximization objective with unit profit for doors being $500 and unit profit for windows being $400. Assume that you are given the Answer report and Sensitivity report in TAB Q2S and Q2A. Answer parts (a)-(e) below Microsoft Excel 16.0 Sensitivity Report Worksheet: Variable Cells Final Reduced Objective Allowable Allowable Cell Name Value Cost Coefficient Increase Decrease $B$3 Variables Qty Doors 20 0 500 300 233.3333333 $C$3 Variables Qty Windows 40 0 400 350 150 Constraints Final Shadow Constraint Allowable Allowable Cell Name Value Price R.H. Side Increase Decrease SD$7 Cutting Used 40 350 40 40 13.33333333 $D$8 Sanding Used 40 30 40 6.666666667 20 $D$9 Finishing Used 50 0 60 LE+30 10 Question part a) If the unit profit on doors increased to $700 would the optimal solution change? Why or why not? Answer part a) > > > > > > Question part b) If the unit profit on doors increased to $700 what is the maximum profit? Answer part b) > > > > Question part c) If the unit profit on windows decreased to $200 would the optimal solution change? Why or why not?Answer part c) > > > > > Question part d) If 20 additional hours of cutting capacity became available in a given week, how much additional profit could the company earn? Answer part d) > > > > Question part e) Suppose another company wanted to use 15 hours of XYZ's sanding capacity in a week and was willing to pay $400 per hour to acquire it. Should Company XYZ agree to this? Why or why not? Answer part e) > > > >Microsoft Excel 16.0 Answer Report Worksheet: Result: Solver found a solution. All Constraints and optimality conditions are satisfied. Solver Engine Engine: Simplex LP Solution Time: 0.016 Seconds. Iterations: 2 Subproblems: 0 Solver Options Max Time Unlimited, Iterations Unlimited, Precision 0.000001, Use Automatic Scaling Max Subproblems Unlimited, Max Integer Sols Unlimited, Integer Tolerance 1%, Assume NonNegative Objective Cell (Max) Cell Name Original Value Final Value SD$4 Unit profit Total Profit 0 26000 Variable Cells Cell Name Original Value Final Value Integer $B$3 Variables Qty Doors 0 20 Contin $C$3 Variables Qty Windows 0 40 Contin Constraints Cell Name Cell Value Formula Status Slack $D$7 Cutting Used 40 $D$7