We have a large-scale optimization problem (~10K vars and ~10K constraints) in the form of LP format file
(generated using Cplex
library).
We wanted to solve that problem file using Cvxpy
(with Gurobi
solver - Note: Cvxpy
is unavoidable), which doesn't accepts LP format file
directly (rather constraint matrices/list).
So, is it possible to somehow read (/transform/parse) that LP format file
into regular Numpy matrices
?
scipy.sparse
is what you are interested in (cvxpy supports both). 3) The task itself is 99% LP-format parsing, so focus on finding an accessible parser (in python). $\endgroup$Cvxpy
is unavoidable becauseCvxpy
does clever transformations which stabilizes and significantly reduces runtime for our large-scale problem $\endgroup$