I have ~30 non-negative variables and 24 equations and I want to find out the upper and lower bound for each variable. Feasible solutions are guaranteed.
So for each variable, I solve two LP problem, one for min and one for max
$$ \begin{array}{rl} \min & c^T x\\ \textrm{s.t.} & Ax = b\\ &x\geq0 \end{array} $$
where $c=(0, 0, \dots, 0, 1, 0, \dots, 0)^T$ and $(0, 0, \dots, 0, -1, 0, \dots, 0)^T$.
So in total I have 60 LPs with exactly the same constraint, but slightly different objective. I have to do the same thing for each day's data for a few thousand days.
Is there a way to somehow reuse the intermediate results to speed up the calculation? Is it possible to implement using existing Python or R package?
Edit: Just to add that for each day, only the rhs $b$ is different, everything else stays the same.