In general, you solve a problem like this by identifying the vertices of the feasible region. Graphing is often a good way to do it, or you can solve the equations pairwise to identify the x- and y-values that are at the limits of the region.
In the attached graph, the solution spaces of the last two constraints are shown in red and blue, and their overlap is shown in purple. Hence the vertices of the feasible region are the vertices of the purple area: (0, 0), (0, 1), (1.5, 1.5), and (3, 0).
The signs of the variables in the contraint function (+ for x, - for y) tell you that to maximize C, you want to make y as small as possible, while making x as large as possible at the same time. The solution space vertex that does that is (3, 0).
To solve a problem like this, we can identify the vertices of the feasible region.
The vertex that satisfies this is (3, 0). Therefore, the maximum value of C is 3.
The feasible region is the area where all the constraints are satisfied. In this case, the feasible region is the purple area in the graph. The vertices of the feasible region are (0, 0), (0, 1), (1.5, 1.5), and (3, 0).
To maximize C, we want to make y as small as possible and x as large as possible. The vertex that satisfies this is (3, 0). Therefore, the maximum value of C is 3.
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A. 2X+5X+7-3
B. 4X-2Y=10X
C. 2P+12+2P-8
Answer:
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Step-by-step explanation: