1 24 The LP problem whose output follows determines how many

1. (24) The LP problem whose output follows determines how many necklaces, bracelets, rings, and earrings a jewelry store should stock (measured in stocking units). The objective function measures profit; it is assumed that every piece stocked will be sold. Constraint 1 measures display space capacity in units, constraint 2 measures time to set up the display in minutes. Constraints 3 and 4 are marketing restrictions.
MAX 100X1+120X2+150X3+125X4
1) X1+2X2+2X3+2X4<108
2) 3X1+5X2+X4<120
3) X1+X3<25
4) X2+X3+X4>50 plus nonnegativity

Target Cell (Max)

Adjustable Cells

Constraints

Use the output to answer the following questions:

A) What is the optimal solution and what profit will it return?
B) How much would you be willing to pay to reduce the setup time restriction by 20 minutes?
C) If the profit for 1 unit of necklace were to drop by $10 what impact will this have?
D) Do the same for earrings?
E) What is the profit for necklaces and the profit for rings if both prices were to drop by $5? What could we say then?
F) The jewelry store is considering having watches as well. Watches take up 3 units of space and one unit of set up time. They also contribute one unit to each of the marketing restrictions (rhs decreases by 1 for each). How much profit would be needed to make it worthwhile to store watches?
G) you are offered the chance to obtain more space. The offer is for 15 units and the total price is 1,000. What should you do? How about 16 units for the same price?
H) How would the solution change if the profit for the bracelets was to increase to 122/unit? What about profit?

Cell Name Final Value
$B$9 Profit 7475

Solution

MAX 100X1+120X2+150X3+125X4

                S.T.

                1) X1+2X2+2X3+2X4<108

                2) 3X1+5X2+X4<120

                3) X1+X3<25

                4) X2+X3+X4>50

                OPTIMAL SOLUTION

                Objective Function Value =          7475.000

Variable

Value

Reduced Cost

X1

8.000

0.000

X2

0.000

5.000

X3

17.000

0.000

X4

33.000

0.000

Constraint

Slack/Surplus

Dual Price

1

0.000

75.000

2

63.000

   0.000

3

0.000

25.000

4

0.000

-25.000

                OBJECTIVE COEFFICIENT RANGES

Variable

Lower Limit

Current Value

Upper Limit

X1

87.500

100.000

No Upper Limit

X2

No Lower Limit

120.000

125.000

X3

125.000

150.000

162.500

X4

120.000

125.000

150.000

                RIGHT HAND SIDE RANGES

Constraint

Lower Limit

Current Value

Upper Limit

1

100.000

108.000

123.750

2

57.000

120.000

No Upper Limit

3

    8.000

25.000

58.000

4

41.500

50.000

54.000

Variable

Value

Reduced Cost

X1

8.000

0.000

X2

0.000

5.000

X3

17.000

0.000

X4

33.000

0.000

1. (24) The LP problem whose output follows determines how many necklaces, bracelets, rings, and earrings a jewelry store should stock (measured in stocking uni
1. (24) The LP problem whose output follows determines how many necklaces, bracelets, rings, and earrings a jewelry store should stock (measured in stocking uni
1. (24) The LP problem whose output follows determines how many necklaces, bracelets, rings, and earrings a jewelry store should stock (measured in stocking uni
1. (24) The LP problem whose output follows determines how many necklaces, bracelets, rings, and earrings a jewelry store should stock (measured in stocking uni

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