Low level interface for Mixed-Integer Quadratic Programs and Mixed-Integer Linerar Programs optimization solvers.
python setup.py install
It is possible to define quadratic programs of the form
minimize (1/2) x' P x + q' x
subject to l <= A x <= u
x[i] \in Z for i in I_idx
i_l[i] <= x[i] <= i_u[i] for i in I_idx
with
from mathprogbasepy import *
# Define problem data
# ...
p = QuadprogProblem(P, q, A, l, u, i_idx, i_l, i_u)
results = p.solve(solver = OSQP)
The current version is 0.1.1
The supported solvers at the moment are: OSQP
, GUROBI
, CPLEX
, MOSEK
, qpOASES
.
Matrices P
and A
are in scipy sparse format. vectors q
, l
and u
are numpy arrays.