In the following problem, the objective function does not have a maximum. However, the problem is stated in canonical form with basic variables x1 and x2 already with a basic feasible solution, so we can start attempting the simplex method and see where it goes wrong. maximize z = −4x3 + 6x4 s.t. x2 − 6x3 + 2x4= 6 x1 + 2x3 − x4 = 5 x1, x2, x3, x4 ≥ 0 Attempt the simplex method. After pivoting to the first adjacent vertex and then attempting to go to the next, what different happens in this problem that didn’t in the other examples? Justify why it would imply the objective is unbounded
In the following problem, the objective function does not have a maximum. However, the problem is stated in canonical form with basic variables x1 and x2 already with a basic feasible solution, so we can start attempting the simplex method and see where it goes wrong. maximize z = −4x3 + 6x4 s.t. x2 − 6x3 + 2x4= 6 x1 + 2x3 − x4 = 5 x1, x2, x3, x4 ≥ 0 Attempt the simplex method. After pivoting to the first adjacent vertex and then attempting to go to the next, what different happens in this problem that didn’t in the other examples? Justify why it would imply the objective is unbounded
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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In the following problem, the objective function does not have a maximum. However,
the problem is stated in canonical form with basic variables x1 and x2 already with a
basic feasible solution, so we can start attempting the simplex method and see where it
goes wrong.
maximize z = −4x3 + 6x4
s.t. x2 − 6x3 + 2x4= 6
x1 + 2x3 − x4 = 5
x1, x2, x3, x4 ≥ 0
Attempt the simplex method. After pivoting to the first adjacent vertex and then
attempting to go to the next, what different happens in this problem that didn’t in the
other examples? Justify why it would imply the objective is unbounded
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