Post-optimality analysis: Change in one of the constraints

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Homework Help Overview

The discussion revolves around a linear programming (LP) problem involving the maximization of a function subject to specific constraints. The original poster has solved the problem using dual simplex and found an optimal solution. They are now exploring how changes to one of the constraints might affect the optimal solution without re-solving the entire problem.

Discussion Character

  • Exploratory, Assumption checking

Approaches and Questions Raised

  • Participants discuss the implications of modifying the first constraint of the LP. The original poster attempts to introduce a new variable to reformulate the constraints but finds it unhelpful. Others seek clarification on the meaning of the modified constraints and question their feasibility.

Discussion Status

Some participants have provided insights into the implications of the modified constraints, noting that one of the conditions is equivalent to the original constraint, while the other is deemed infeasible. There is an ongoing exploration of the reasoning behind these conclusions, with participants engaging in clarifying the conditions presented.

Contextual Notes

The discussion includes considerations of the feasibility of constraints and the implications of the non-negativity conditions on the variables involved. Participants are examining the logical consistency of the proposed modifications to the original problem.

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.
 

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