In: Statistics and Probability
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Final |
Reduced |
Objective |
Allowable |
Allowable |
||||
Cell |
Name |
Value |
Cost |
Coefficient |
Increase |
Decrease |
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$B$6 |
X1 |
45 |
0 |
12 |
10 |
8 |
||
$C$6 |
X2 |
0 |
-6 |
8 |
15 |
12 |
||
$D$6 |
X3 |
10 |
0 |
5 |
20 |
15 |
||
$E$6 |
X4 |
35 |
0 |
6 |
8 |
10 |
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Constraints |
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Final |
Shadow |
Constraint |
Allowable |
Allowable |
||||
Cell |
Name |
Value |
Price |
R.H. Side |
Increase |
Decrease |
||
Const1 |
74 |
12 |
74 |
50 |
20 |
|||
Const2 |
54 |
8.5 |
54 |
42 |
40 |
|||
Const3 |
35 |
-5 |
35 |
25 |
20 |
|||
Conts4 |
80 |
0 |
120 |
30 |
25 |
(a) What is the objective
function? You will write the algebraic version like
Z= 2X1+ 3X2+…etc (10)
(b) What is the
optimal solution, and the optimal value of the objective function?
(15)
(b) Can we make
the following change to the RHS of the constraints as follows:
(20)
const. 1 +20
const. 2 -10
const. 3 -5
If so, what is the value of the objective function after the
change. (you will show FULL work)
(a) The objective function will be given by the objective coefficients in the first table:
(b) The optimal solution is given by the final value column in the first table:
(c) The change should be compared against the allowable increase if positive or the allowable decrease if negative as given in the second table. As multiple constraints are changing, we have to add up the fraction of change to the allowed change. If the sum is less than 1, the change is allowed.
Constraint 1: Increase: Fraction = Increase / Allowed increase = 20 / 50 = 0.4
Constraint 2: Decrease: Fraction = Decrease / Allowed decrease = 10 / 40 = 0.25
Constraint 3: Decrease: Fraction = Decrease / Allowed decrease = 5 / 20 = 0.25
Total fraction = 0.4 + 0.25 + 0.25 = 0.9 < 1
So, the change is allowed.
So, the objective function change is calculated by multiplying each increase / decrease by the corresponding shadow price from the second table.
So, the new value of the objective function will be 980.