(0, 2) (0, 0) (3, 3) (6,3) (6,0) X₁ Label each of the following statements as True or False, and then justify your answer based on the graphical method. In each case, give an example of an objective function that illustrates your answer. (a) If (3, 3) produces a larger value of the objective function than (0, 2) and (6, 3), then (3, 3) must be an optimal solution. (b) If (3, 3) is an optimal solution and multiple optimal solu- tions exist, then either (0, 2) or (6, 3) must also be an opti- mal solution. (c) The point (0, 0) cannot be an optimal solution.
(0, 2) (0, 0) (3, 3) (6,3) (6,0) X₁ Label each of the following statements as True or False, and then justify your answer based on the graphical method. In each case, give an example of an objective function that illustrates your answer. (a) If (3, 3) produces a larger value of the objective function than (0, 2) and (6, 3), then (3, 3) must be an optimal solution. (b) If (3, 3) is an optimal solution and multiple optimal solu- tions exist, then either (0, 2) or (6, 3) must also be an opti- mal solution. (c) The point (0, 0) cannot be an optimal solution.
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
Related questions
Question
Transcribed Image Text:x2
(0, 2)
(0, 0)
(3, 3)
(6,3)
(6,0) X₁
Label each of the following statements as True or False, and
then justify your answer based on the graphical method. In each
case, give an example of an objective function that illustrates
your answer.
(a) If (3, 3) produces a larger value of the objective function than
(0, 2) and (6, 3), then (3, 3) must be an optimal solution.
(b) If (3, 3) is an optimal solution and multiple optimal solu-
tions exist, then either (0, 2) or (6, 3) must also be an opti-
mal solution.
(c) The point (0, 0) cannot be an optimal solution.
Transcribed Image Text:3.2-2. The shaded area in the following graph represents the feasi-
ble region of a linear programming problem whose objective func-
tion is to be maximized.
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