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QUESTION 1

Which of the following is true about linear programming
problems:

Linear
programming problems may have multiple goals or objectives specified

Linear
programming problems always have an objective function and at least two
constraints

Linear
programming problems always involve maximizing an objective function

Linear
programming problems always involve minimizing an objective function

None
of the above

QUESTION 2

A manager should know the following things about linear
programming:

What
it is

When
it should be used

When
it should not be used

How
to interpret the results of a study

All
of the above

QUESTION 3

When formulating a linear programming problem on a
spreadsheet, which of the following is true?

The
data cells will show the optimal solution

The
data cells contain the model parameters

The
objective cells will show the levels of activities for the decision being made

The
objective cell will decrease as the objective function line is moved away from
the origin

All
of the above

QUESTION 4

To answer the question, refer to the following spreadsheet:

image

Where are the output cells located?

B2:C2

B2:C2
and B5:C7

B10:C10

F10

None
of the above

QUESTION 5

A linear programming problem where the objective is to match
employees to an equal number of tasks at a minimum costs is called:

A
resource-allocation problem

A
matching problem

An
assignment problem

A
cost-benefit tradeoff problem

None
of the above

QUESTION 6

What is the optimal solution for the following problem?

Minimize

P = 3x + 15y

subject to

2x + 4y ? 12

5x + 2y ? 10

and

x ? 0, y ? 0.

(x, y) = (2, 0)

(x, y) = (0, 3)

(x, y) = (0, 0)

(x, y) = (1, 2.5)

(x, y) = (6, 0)

QUESTION 7

Which of the following is NOT a component of a linear
programming model?

Functional constraint

Non negativity constraint

Optimal constraint

Decision variable

None of the above

QUESTION 8

Which of the following is NOT true about linear programming
problems:

Linear
programming problems can be formulated both algebraically as a mathematical
model and on spreadsheets

A
mathematical model will be an exact representation of the real problem

Approximations
and simplifying assumptions generally are required to have a workable linear
programming model

In
the algebraic form of a resource constraint, the coefficient of each decision
variable is the resource usage per unit of the corresponding capacity

None
of the above

QUESTION 9

The production planner for Fine Coffees, Inc. produces two
coffee blends: American (A) and British (B). He can only get 300 pounds of
Colombian beans per week and 200 pounds of Dominican beans per week. Each pound
of American blend coffee requires 12 ounces of Colombian beans and 4 ounces of
Dominican beans, while a pound of British blend coffee uses 8 ounces of each
type of bean. Profits for the American blend are $2.00 per pound, and profits
for the British blend are $1.00 per pound.

What is the constraint for Colombian beans?

A
+ 2B ? 4,800

12A
+ 8B ? 4,800

2A
+ B ? 4,800

8A
+ 12B ? 4,800

4A
+ 8B ? 4,800

QUESTION 10

Which of the following could NOT be a constraint for a
linear programming problem?

1X
+ 2Y ? 3

1X
+ 2Y ? 3

1X
+ 2Y = 3

1X
+ 2Y

1X
+ 2Y + 3Z ? 3

QUESTION 11

An electronics firm produces two models of pocket
calculators: the A-100 (A) and the B-200 (B). Each model uses one circuit
board, of which there are only 2,500 available for this week’s production. In
addition, the company has allocated a maximum of 800 hours of assembly time
this week for producing these calculators. Each A-100 requires 15 minutes to
produce while each B-200 requires 30 minutes to produce. The firm forecasts
that it could sell a maximum of 4,000 of the A-100s this week and a maximum of
1,000 B-200s. Profits for the A-100 are $1.00 each and profits for the B-200
are $4.00 each.

What is the objective function?

P
= 4A + 1B

P
= 0.25A +1B

P
= 1A + 4B

P
= 1A + 1B

P
= 0.25A + 0.5B

QUESTION 12

In linear programming, the solution that does not violate
any constraints and is the best according to the objective function is referred
to as:

Optimal

Feasible

Non negative

Targeted

All of the above

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