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

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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:-
- Equalize each constraint and determine the values of x1 and x2.
- Plot all these values on the graph.
- Find the corner points along the feasible region.
- 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.
Step by step
Solved in 3 steps with 2 images
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