Linear programming
In a linear programming problem, the constraints represent the limitations on the situation, and the objective function is the function being maximized (or minimized). The constraints are inequalities, so a graph with all constraints shown on it will be a region, called the feasible region. The maximum or minimum value of the objective function will always happen at one of the vertices (corners) of the feasible region, so the corner points are the ones you need to check.Be sure you understand how to write constraints as well as an objective function for a real-world problem, such as one in which cost is minimized and profit is maximized. Be sure you understand how to test the vertices of the feasible region in the objective function to find the solution.
problems below
1. Graph the system of constraints and find the value of x and y that maximize the objective
function.
(1 point)
x20
y20
Constraints 1
yS-x+2
52 y+x
Objective function: C = 7x – 3y
(2.5, 2.5)
(0, 2)
(0,0)
(5,0)
2. Your computer supply store sells two types of inkjet printers. The first, type A, costs $237 and (1 point)
you make a $22 profit on each one. The second, type B, costs $122 and you make a $19 profit
on each one. You can order no more than 120 printers this month, and you need to make at
least $2,400 profit on them. If you must order at least one of each type of printer, how many of
each type of printer should you order if you want to minimize your cost?
69 of type A : 51 of type B
40 of type A : 80 of type B
51 of type A : 69 of type B
80 of type A : 40 of type B
(1 point)
3. A factory can produce two products, x and y, with a profit approximated by P = 14x + 22y –
900. The production of y can exceed x by no more than 200 units. Moreover, production levels
are limited by the formula x + 2y = 1600. What production levels yield maximum profit?
Ox = 400
y = 600
Ox=0
y = 0
x= 1600
y=0
Ox=0
y=200
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