example 1a 1.plot all the corner points for the feasible area. 2. Find the optimum solution to  X= Y= VALUE Z=

Practical Management Science
6th Edition
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Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
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example 1a

1.plot all the corner points for the feasible area.

2. Find the optimum solution to 

X=

Y=

VALUE Z=

L.P. Model:
Minimize
Subject to:
Z = 6X+7Y
1X + 2Y ≥ 40
3X+1Y275
X,Y 20
(C₁)
(C₂)
On the graph on right, constraints C, and C₂ have been
plotted.
Using the point drawing tool, plot all the corner points for
the feasible area.
(…..)
A
100-
90-
80-
70-C2
60-
50-
40-
30-
20-
10+
0-
0
LO
10
d:
20 30 40
50
X
60 70 80 90
Transcribed Image Text:L.P. Model: Minimize Subject to: Z = 6X+7Y 1X + 2Y ≥ 40 3X+1Y275 X,Y 20 (C₁) (C₂) On the graph on right, constraints C, and C₂ have been plotted. Using the point drawing tool, plot all the corner points for the feasible area. (…..) A 100- 90- 80- 70-C2 60- 50- 40- 30- 20- 10+ 0- 0 LO 10 d: 20 30 40 50 X 60 70 80 90
Expert Solution
Step 1 Introduction;-

Linear programming is a mathematical technique that is also used in operations management departments. This technique is commonly used to find the best outcome with the maximum profit. Linear programming has various methods; each method is chosen by the companies as per their requirements or based on different factors.

Steps to solve the graphical problem:- 

  1. Equalize each constraint and determine the values of x1 and x2.
  2. Plot all these values on the graph. 
  3. Find the corner points along the feasible region.
  4. Determine the minimum/maximum value from the outcomes.

Below is the solution by using these steps.

Plotting values on the graph:-

Plotting all the above-determined values of each constraint on the graph. Finding the feasible region. The constrain line that is (<=) will be shared towards the origin (0,0) and the constraint that has (>=) will shade opposite to the origin (0,0). The common region of all their three lines of constraint will be the feasible region.

Corner points of the feasible region:- Fill the values of x1 and x2 in the objective function. Then choose the minimum/maximum (as per the objective function) value from the outcomes of the objective function.

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