The underlying solver to use.
This must stay synchronized with math_opt_parameters_pb2.SolverTypeProto.
Attributes:
GSCIP: Solving Constraint Integer Programs (SCIP) solver (third party).
Supports LP, MIP, and nonconvex integer quadratic problems. No dual data
for LPs is returned though. Prefer GLOP for LPs.
GUROBI: Gurobi solver (third party). Supports LP, MIP, and nonconvex integer
quadratic problems. Generally the fastest option, but has special
licensing, see go/gurobi-google for details.
GLOP: Google's Glop linear solver. Supports LP with primal and dual simplex
methods.
CP_SAT: Google's CP-SAT solver. Supports problems where all variables are
integer and bounded (or implied to be after presolve). Experimental
support to rescale and discretize problems with continuous variables.
MOE:begin_intracomment_strip
PDLP: Google's PDLP solver. Supports LP and convex diagonal quadratic
objectives. Uses first order methods rather than simplex. Can solve very
large problems.
MOE:end_intracomment_strip
GLPK: GNU Linear Programming Kit (GLPK) (third party). Supports MIP and LP.
Thread-safety: GLPK use thread-local storage for memory allocations. As a
consequence when using IncrementalSolver, the user must make sure that
instances are closed on the same thread as they are created or GLPK will
crash. To do so, use `with` or call IncrementalSolver#close(). It seems OK
to call IncrementalSolver#Solve() from another thread than the one used to
create the Solver but it is not documented by GLPK and should be avoided.
Of course these limitations do not apply to the solve() function that
recreates a new GLPK problem in the calling thread and destroys before
returning. When solving a LP with the presolver, a solution (and the
unbound rays) are only returned if an optimal solution has been found.
Else nothing is returned. See glpk-5.0/doc/glpk.pdf page #40 available
from glpk-5.0.tar.gz for details.
OSQP: The Operator Splitting Quadratic Program (OSQP) solver (third party).
Supports continuous problems with linear constraints and linear or convex
quadratic objectives. Uses a first-order method.
ECOS: The Embedded Conic Solver (ECOS) (third party). Supports LP and SOCP
problems. Uses interior point methods (barrier).
SCS: The Splitting Conic Solver (SCS) (third party). Supports LP and SOCP
problems. Uses a first-order method.
HIGHS: The HiGHS Solver (third party). Supports LP and MIP problems (convex
QPs are unimplemented).
SANTORINI: The Santorini Solver (first party). Supports MIP. Experimental,
do not use in production.
Definition at line 34 of file parameters.py.
|
| | GSCIP = math_opt_parameters_pb2.SOLVER_TYPE_GSCIP |
| | GUROBI = math_opt_parameters_pb2.SOLVER_TYPE_GUROBI |
| | GLOP = math_opt_parameters_pb2.SOLVER_TYPE_GLOP |
| | CP_SAT = math_opt_parameters_pb2.SOLVER_TYPE_CP_SAT |
| | PDLP = math_opt_parameters_pb2.SOLVER_TYPE_PDLP |
| | GLPK = math_opt_parameters_pb2.SOLVER_TYPE_GLPK |
| | OSQP = math_opt_parameters_pb2.SOLVER_TYPE_OSQP |
| | ECOS = math_opt_parameters_pb2.SOLVER_TYPE_ECOS |
| | SCS = math_opt_parameters_pb2.SOLVER_TYPE_SCS |
| | HIGHS = math_opt_parameters_pb2.SOLVER_TYPE_HIGHS |
| | SANTORINI = math_opt_parameters_pb2.SOLVER_TYPE_SANTORINI |
1.15.0