Post-optimality analysis: Change in one of the constraints

drawar
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Homework Statement



Consider the LP:

max \, -3x_1-x_2
\,\,s.t. \,\,\,\, 2x_1+x_2 \leq 3
\quad \quad \ -x_1+x_2 \geq 1
\quad \quad \quad \quad \ x_1,x_2 \geq 0Suppose I have solved the above problem for the optimal solution. (I used dual simplex and get (0,1) as the optimal solution.)
Now if the first constraint (2x_1+x_2 \leq 3) is either changed to

(1) max \, (2x_1+x_2,0) \leq 3, or
(2) max \, (2x_1+x_2,6)\leq 3,

is it possible to obtain the new optimal solution without having to solve the entire problem from the scratch?

Homework Equations


The Attempt at a Solution

I have tried introducing a new variable t to address the maximum and rewrite the constraints in linear form but it doesn't seem to help.

Any hint or comment is greatly appreciated, thank you!
 
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Your optimal solution of ##(0,1)## is correct for the first part yielding a max of ##-1##. Could you elaborate on conditions (1) and (2) a bit more? I'm not quite sure what the ##', 0)'## and ##', 6)'## translate to.
 
conditions (1) should read "the larger of (2x_1+x_2) and 0 is smaller than 3", that is, if 0 \leq 2x_1+x_2 then we also have 0 \leq 2x_1+x_2 \leq 3, otherwise, if 2x_1+x_2 \leq 0 then 2x_1+x_2 \leq 0.
 
drawar said:

Homework Statement



Consider the LP:

max \, -3x_1-x_2
\,\,s.t. \,\,\,\, 2x_1+x_2 \leq 3
\quad \quad \ -x_1+x_2 \geq 1
\quad \quad \quad \quad \ x_1,x_2 \geq 0


Suppose I have solved the above problem for the optimal solution. (I used dual simplex and get (0,1) as the optimal solution.)
Now if the first constraint (2x_1+x_2 \leq 3) is either changed to

(1) max \, (2x_1+x_2,0) \leq 3, or
(2) max \, (2x_1+x_2,6)\leq 3,

is it possible to obtain the new optimal solution without having to solve the entire problem from the scratch?



Homework Equations





The Attempt at a Solution




I have tried introducing a new variable t to address the maximum and rewrite the constraints in linear form but it doesn't seem to help.

Any hint or comment is greatly appreciated, thank you!

Since 3 > 0 the constraint ##\max(2x_1+x_2,0) \leq 3## is the same as the simple constraint ##2x_1 + x_2 \leq 3##; can you see why? Anyway, the solution (1,0) satisfies it, so there would be no change in the solution.

The second form ##\max(2x_1+x_2,6)\leq 3## is infeasible. Can you see why no ##x_1, x_2## can possibly satisfy that inequality? (If you changed '##\max##' to '##\min##' you could satisfy it. Again, can you see why?)
 
drawar said:
conditions (1) should read "the larger of (2x_1+x_2) and 0 is smaller than 3", that is, if 0 \leq 2x_1+x_2 then we also have 0 \leq 2x_1+x_2 \leq 3, otherwise, if 2x_1+x_2 \leq 0 then 2x_1+x_2 \leq 0.

If ##2x_1 + x_2 ≤ 0##, there is no maximum.

You simply can't use the second condition.
 
Thank you all, I think I've got what you said,
for (1) since it was given that x_1,x_2 \geq 0, 2x_1+x_2 \geq 0 hence the constraint is equivalent to 2x_1+x_2 \leq 3.

for (2) whatever the larger is, the constraint makes no sense because 6 > 3, so the problem is infeasible. If 'max' were changed to 'min' then the constraint is nothing but 2x_1+x_2 \leq 3.
 
There are two things I don't understand about this problem. First, when finding the nth root of a number, there should in theory be n solutions. However, the formula produces n+1 roots. Here is how. The first root is simply ##\left(r\right)^{\left(\frac{1}{n}\right)}##. Then you multiply this first root by n additional expressions given by the formula, as you go through k=0,1,...n-1. So you end up with n+1 roots, which cannot be correct. Let me illustrate what I mean. For this...

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