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Clarify scipy linprog transformation description #742

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4 changes: 2 additions & 2 deletions lectures/lp_intro.md
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Expand Up @@ -487,9 +487,9 @@ The optimal plan tells the factory to produce $2.5$ units of Product 1 and $5$

We are using the `linprog` function as a *black box*.

Inside it, Python first transforms the problem into standard form.
Internally, after a presolve step, SciPy transforms the problem into a standard form before applying the selected solver.

To do that, for each inequality constraint it generates one slack variable.
In this transformation, one slack variable is added for each inequality constraint.

Here the vector of slack variables is a two-dimensional NumPy array that equals $b_{ub} - A_{ub}x$.

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