(a) Define the decision variables and write the linear programming model for the p
LET 1 X BE OUNCES OF OATS AND HAVE X2 BE OUNCES OF RICE.
WE WANT TO MINIMIZE Z=0.06 X1 + 0.03 X 2
SUBJECT TO 10 X 1 + 6 X 2 > =45
2 X 1 + 3 X 2> = 13
X1>=0
X2>=0
(b) Sketch

Question 1
2 out of 2 points
When using a linear programming model to solve the "diet" problem, the
objective is generally to maximize profit.
Selected
Answer:
e
Correct
Answer:
e
Fals
Fals
Question 2
2 out of 2 points
In a transportation problem, a deman

Reflection to date
The most unexpected thing that I have learned is that Excel is a great tool to use to auto-calculate
numbers when dealing with Statistics as long as the formulas are entered correctly. In addition, I
never paid attention to the fact tha

1.
QUESTION 1
The solution to the LP relaxation of a maximization integer linear
program provides an upper bound for the value of the objective function.
True
False
2 points
1.
QUESTION 2
If exactly 3 projects are to be selected from a set of 5 projects,

Discuss Simulation
Simulation is used in the real world for the development of specialized simulation languages and
to analyze systems. Also, it imitates a real-world model or system. An example of simulation in
my line of work is in our Workforce Departm

Discuss LP Models
According to, Introduction to Management Science, the objective function is a linear
mathematical relationship that describes the objective of the firm in terms of the decision
variables. A constraint is a linear relationship that repres

(a) Define the decision variables and write the linear programming model for the prob
X1 = oats (ounces)
X2 =rice (ounces)
Cereal Box = 45 milligrams of Vitamin A and 13 milligrams of Vitamin B
Oats = 10 milligrams of Vitamin A and 2 milligrams of Vitamin

Hoylake Rescue Squad
Probability of Time between calls
Simulation
Cumulative
(lower
Time between
simulation
Time
Cumulative
P(x)
bound)
calls
Expectations Number
RN
between calls
clock
0.15
0
1
0.15
1
0.635564
0
0
0.1
0.15
2
0.2
2
0.964271
0
0.2
0.25
3
0.

Practice Setting up Linear Programming Models for Business Applications
Problem 14 Let
X1 = ore 1
X2 = ore 2
X3 = ore 3
X4 = ore 4
X5 = ore 5
X6 = ore 6
Minimize: (Cost per ton = 27X1+25X2+32X3+22X4+20X5+24X6)
Subject to Constraints: all X1, X2, X3, X4, X