The plot below again shows the feasible region and the constraint lines. Also, the purple, yellow, and brown lines are associated with objective function values of 1500, 1800, and 2050 respectively. The decision variable x is plotted along the horizontal axis and the decision variable y on the vertical axis. Let the constraints be as follows: Red: 3x + 2y < 30 Green: + 5y < 25 Blue: + y ≤7 Determine the optimal solution. Enter below the value of the x decision variable in the optimal solution. 14 12 10 8 CO 6 0 0 2 4 6 8 10 12 14

The plot below again shows the feasible region and the constraint lines. Also, the purple, yellow, and brown lines are associated with objective function values of 1500, 1800, and 2050 respectively. The decision variable x is plotted along the horizontal axis and the decision variable y on the vertical axis. Let the constraints be as follows: Red: 3x + 2y < 30 Green: + 5y < 25 Blue: + y ≤7 Determine the optimal solution. Enter below the value of the x decision variable in the optimal solution. 14 12 10 8 CO 6 0 0 2 4 6 8 10 12 14

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Question

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Continuing from the problem above, enter below the value of the y decision variable in the optimal solution.

In thinking about the feasible region of a linear programming model, you are guaranteed that the optimal solution will be located at an extreme or corner point

The plot below again shows the feasible region and the constraint lines. Also, the purple, yellow, and brown lines are associated with
objective function values of 1500, 1800, and 2050 respectively. The decision variable x is plotted along the horizontal axis and the
decision variable y on the vertical axis. Let the constraints be as follows:
Red: 3x + 2y < 30
Green: + 5y < 25
Blue: + y ≤7
Determine the optimal solution. Enter below the value of the x decision variable in the optimal solution.
14
12
10
8
CO
6
0
0
2
4
6
8
10
12
14

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