# Repeated linear programming with similar (not identical) problems

I have multiple linear programming problems of the form:

$$Minimize\{c^{T}\cdot x\} s.t. Ax = b, x \ge 0$$

Where $$c$$ and $$A$$ are fixed for all the problems. Is there any way to utilize that for a more efficient solution than solving each problem from scratch?

Currently I'm using scipy's linprog but the performance is too slow given the amount of problems (thousands). I was wondering if there's a way to make this feasible with some smart preprocessing.
I've tried searching using terms such as "repeated linear programming", "repeated simplex" etc., but to no avail.

• For future reference, I've asked this question on math overflow where it was proposed to search for warm-start LP solvers and use the dual simplex algorithm. – andersource Aug 18 '20 at 4:25