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128 CHAPTER 3 LINEAR PROGRAMMING: SENSITIVITY ANALYSIS AND INTERPRETATION OF SOLUTION

Figure 3.17 Excel Solution for the Salsa Problem
Original
Name Value Final Value
Maximize total profit 0 1919.642857

Adjustable Cells
Original
Name Value Final Value
Units produced W 0 1250
Units produced M 0 535.7142857

Constraints
Name Cell Value Status Slack
Whole tomatoes grams used (LHS) 280000 Binding 0
Tomato sauce grams used (LHS) 120000 Not Binding 10000
Tomato paste grams used (LHS) 100000 Binding 0
Adjustable Cells
Final Reduced Objective Allowable Allowable
Name Value Cost Coefficient Increase Decrease
Units produced W 1250 0 1 0.25 0.107142857
Units produced M 535.7142857 0 1.25 0.15 0.25

Constraints
Final Shadow Constraint Allowable Allowable
Name Value Price R.H. Side Increase Decrease
Whole tomatoes grams used
(LHS) 280000 0.004464286 280000 70000 10000
Tomato sauce grams used (LHS) 120000 0 130000 1E+30 10000
Tomato paste grams used (LHS) 100000 0.006696429 100000 2500 20000

13 Quality Air Conditioning manufactures three home air conditioners: an economy model,
a standard model and a deluxe model. The profits per unit are E63, E95 and E135,
respectively. The production requirements per unit are as follows:

Number of Number of Cooling Manufacturing Time
Fans Coils (hours)
Economy 1 1 8
Standard 1 2 12
Deluxe 1 4 14

For the coming production period, the company has 200 fan motors, 320 coolling coils
and 2400 hours of manufacturing time available. How many economy models (E),
standard models (S) and deluxe models (D) should the company produce in order to
maximize profit? The linear programming model for the problem is as follows:

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