Update solvers_map's

- add mathopt and cpsat when missing - put them before gurobi and minizinc respectively - remove default args that are already the same in solvers
airbus · Oct 4, 2024 · 2bb04de · 2bb04de
1 parent dda37b4
commit 2bb04de
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Showing 7 changed files with 63 additions and 98 deletions.
diff --git a/discrete_optimization/coloring/coloring_solvers.py b/discrete_optimization/coloring/coloring_solvers.py
@@ -7,16 +7,25 @@
 from typing import Any
 
 from discrete_optimization.coloring.solvers.coloring_asp_solver import ColoringASPSolver
-from discrete_optimization.coloring.solvers.coloring_cp_solvers import (
-    ColoringCP,
-    ColoringCPModel,
-)
+from discrete_optimization.coloring.solvers.coloring_cp_solvers import ColoringCP
 from discrete_optimization.coloring.solvers.coloring_cpsat_solver import (
     ColoringCPSatSolver,
     ModelingCPSat,
 )
-from discrete_optimization.coloring.solvers.coloring_lp_solvers import ColoringLP
+from discrete_optimization.coloring.solvers.coloring_lp_solvers import (
+    ColoringLP,
+    ColoringLPMathOpt,
+)
 from discrete_optimization.coloring.solvers.coloring_solver import SolverColoring
+from discrete_optimization.coloring.solvers.greedy_coloring import (
+    ColoringProblem,
+    GreedyColoring,
+)
+from discrete_optimization.generic_tools.cp_tools import ParametersCP
+from discrete_optimization.generic_tools.do_problem import Problem
+from discrete_optimization.generic_tools.result_storage.result_storage import (
+    ResultStorage,
+)
 
 try:
     import pytoulbar2
@@ -30,45 +39,28 @@
     toulbar2_available = True
 
 
-from discrete_optimization.coloring.solvers.greedy_coloring import (
-    ColoringProblem,
-    GreedyColoring,
-    NXGreedyColoringMethod,
-)
-from discrete_optimization.generic_tools.cp_tools import CPSolverName, ParametersCP
-from discrete_optimization.generic_tools.do_problem import Problem
-from discrete_optimization.generic_tools.lp_tools import ParametersMilp
-from discrete_optimization.generic_tools.result_storage.result_storage import (
-    ResultStorage,
-)
-
 solvers: dict[str, list[tuple[type[SolverColoring], dict[str, Any]]]] = {
     "lp": [
         (
             ColoringLP,
-            {
-                "greedy_start": True,
-                "use_cliques": False,
-                "parameters_milp": ParametersMilp.default(),
-            },
+            {},
         ),
-    ],
-    "cp": [
         (
-            ColoringCP,
-            {
-                "cp_solver_name": CPSolverName.CHUFFED,
-                "cp_model": ColoringCPModel.DEFAULT,
-                "parameters_cp": ParametersCP.default(),
-                "object_output": True,
-            },
+            ColoringLPMathOpt,
+            {},
         ),
+    ],
+    "cp": [
         (
             ColoringCPSatSolver,
             {"modeling": ModelingCPSat.BINARY, "parameters_cp": ParametersCP.default()},
         ),
+        (
+            ColoringCP,
+            {},
+        ),
     ],
-    "greedy": [(GreedyColoring, {"strategy": NXGreedyColoringMethod.best})],
+    "greedy": [(GreedyColoring, {})],
     "asp": [(ColoringASPSolver, {"time_limit": 5})],
 }
 if toulbar2_available:

diff --git a/discrete_optimization/facility/facility_solvers.py b/discrete_optimization/facility/facility_solvers.py
@@ -15,7 +15,7 @@
 from discrete_optimization.facility.solvers.facility_lp_solver import (
     LP_Facility_Solver,
     LP_Facility_Solver_CBC,
-    ParametersMilp,
+    LP_Facility_Solver_MathOpt,
 )
 from discrete_optimization.facility.solvers.facility_solver import SolverFacility
 from discrete_optimization.facility.solvers.greedy_solvers import (
@@ -30,23 +30,17 @@
 
 solvers: dict[str, list[tuple[type[SolverFacility], dict[str, Any]]]] = {
     "lp": [
+        (
+            LP_Facility_Solver_MathOpt,
+            {},
+        ),
         (
             LP_Facility_Solver,
-            {
-                "parameters_milp": ParametersMilp.default(),
-                "use_matrix_indicator_heuristic": True,
-                "n_shortest": 10,
-                "n_cheapest": 10,
-            },
+            {},
         ),
         (
             LP_Facility_Solver_CBC,
-            {
-                "parameters_milp": ParametersMilp.default(),
-                "use_matrix_indicator_heuristic": True,
-                "n_shortest": 10,
-                "n_cheapest": 10,
-            },
+            {},
         ),
     ],
     "cp": [

diff --git a/discrete_optimization/knapsack/knapsack_solvers.py b/discrete_optimization/knapsack/knapsack_solvers.py
@@ -4,7 +4,6 @@
 
 from typing import Any
 
-from discrete_optimization.generic_tools.cp_tools import CPSolverName
 from discrete_optimization.generic_tools.do_problem import Problem
 from discrete_optimization.generic_tools.lp_tools import ParametersMilp
 from discrete_optimization.generic_tools.result_storage.result_storage import (
@@ -18,6 +17,9 @@
 from discrete_optimization.knapsack.solvers.dyn_prog_knapsack import KnapsackDynProg
 from discrete_optimization.knapsack.solvers.greedy_solvers import GreedyBest
 from discrete_optimization.knapsack.solvers.knapsack_asp_solver import KnapsackASPSolver
+from discrete_optimization.knapsack.solvers.knapsack_cpsat_solver import (
+    CPSatKnapsackSolver,
+)
 from discrete_optimization.knapsack.solvers.knapsack_solver import SolverKnapsack
 from discrete_optimization.knapsack.solvers.lp_solvers import (
     KnapsackORTools,
@@ -33,10 +35,11 @@
     ],
     "greedy": [(GreedyBest, {})],
     "cp": [
-        (CPKnapsackMZN, {"cp_solver_name": CPSolverName.CHUFFED}),
-        (CPKnapsackMZN2, {"cp_solver_name": CPSolverName.CHUFFED}),
+        (CPSatKnapsackSolver, {}),
+        (CPKnapsackMZN, {}),
+        (CPKnapsackMZN2, {}),
     ],
-    "asp": [(KnapsackASPSolver, {"time_limit": 100})],
+    "asp": [(KnapsackASPSolver, {})],
     "dyn_prog": [
         (
             KnapsackDynProg,

diff --git a/discrete_optimization/maximum_independent_set/mis_solvers.py b/discrete_optimization/maximum_independent_set/mis_solvers.py
@@ -6,8 +6,6 @@
 
 from typing import Any
 
-from discrete_optimization.coloring.solvers.coloring_cpsat_solver import ModelingCPSat
-from discrete_optimization.generic_tools.cp_tools import ParametersCP
 from discrete_optimization.generic_tools.lp_tools import ParametersMilp
 from discrete_optimization.generic_tools.result_storage.result_storage import (
     ResultStorage,
@@ -30,7 +28,6 @@
 from discrete_optimization.maximum_independent_set.solvers.mis_solver import MisSolver
 from discrete_optimization.maximum_independent_set.solvers.mis_toulbar import (
     MisToulbarSolver,
-    toulbar_available,
 )
 
 solvers: dict[str, list[tuple[type[MisSolver], dict[str, Any]]]] = {
@@ -48,10 +45,10 @@
             },
         ),
     ],
-    "ortools": [
+    "cp": [
         (
             MisOrtoolsSolver,
-            {"modeling": ModelingCPSat.BINARY, "parameters_cp": ParametersCP.default()},
+            {},
         ),
     ],
     "networkX": [(MisNetworkXSolver, {})],

diff --git a/discrete_optimization/rcpsp/rcpsp_solvers.py b/discrete_optimization/rcpsp/rcpsp_solvers.py
@@ -21,7 +21,6 @@
     ParametersAltGa,
     ParametersGa,
 )
-from discrete_optimization.generic_tools.lp_tools import ParametersMilp
 from discrete_optimization.generic_tools.result_storage.result_storage import (
     ResultStorage,
 )
@@ -44,7 +43,6 @@
     LP_RCPSP_MATHOPT,
 )
 from discrete_optimization.rcpsp.solver.rcpsp_pile import (
-    GreedyChoice,
     PileSolverRCPSP,
     PileSolverRCPSP_Calendar,
 )
@@ -59,51 +57,35 @@
     "lp": [
         (
             LP_RCPSP_MATHOPT,
-            {
-                "parameters_milp": ParametersMilp.default(),
-            },
+            {},
         ),
         (
             LP_MRCPSP_MATHOPT,
-            {
-                "parameters_milp": ParametersMilp.default(),
-            },
+            {},
         ),
     ],
     "greedy": [
-        (PileSolverRCPSP, {"greedy_choice": GreedyChoice.MOST_SUCCESSORS}),
-        (PileSolverRCPSP_Calendar, {"greedy_choice": GreedyChoice.MOST_SUCCESSORS}),
+        (PileSolverRCPSP, {}),
+        (PileSolverRCPSP_Calendar, {}),
     ],
     "cp": [
+        (CPSatRCPSPSolver, {"parameters_cp": ParametersCP.default()}),
         (
             CP_RCPSP_MZN,
-            {
-                "cp_solver_name": CPSolverName.CHUFFED,
-                "parameters_cp": ParametersCP.default(),
-            },
+            {},
         ),
         (
             CP_MRCPSP_MZN,
-            {
-                "cp_solver_name": CPSolverName.CHUFFED,
-                "parameters_cp": ParametersCP.default(),
-            },
+            {},
         ),
         (
             CP_RCPSP_MZN_PREEMPTIVE,
-            {
-                "cp_solver_name": CPSolverName.CHUFFED,
-                "parameters_cp": ParametersCP.default(),
-            },
+            {},
         ),
         (
             CP_MRCPSP_MZN_PREEMPTIVE,
-            {
-                "cp_solver_name": CPSolverName.CHUFFED,
-                "parameters_cp": ParametersCP.default(),
-            },
+            {},
         ),
-        (CPSatRCPSPSolver, {"parameters_cp": ParametersCP.default()}),
     ],
     "critical-path": [(CPM, {})],
     "lns-scheduling": [

diff --git a/discrete_optimization/rcpsp_multiskill/rcpsp_multiskill_solvers.py b/discrete_optimization/rcpsp_multiskill/rcpsp_multiskill_solvers.py
@@ -24,6 +24,9 @@
     CP_MS_MRCPSP_MZN,
     CP_MS_MRCPSP_MZN_PREEMPTIVE,
 )
+from discrete_optimization.rcpsp_multiskill.solvers.cpsat_msrcpsp_solver import (
+    CPSatMSRCPSPSolver,
+)
 from discrete_optimization.rcpsp_multiskill.solvers.lp_model import (
     LP_Solver_MRSCPSP_MathOpt,
 )
@@ -35,39 +38,33 @@
     "lp": [
         (
             LP_Solver_MRSCPSP_MathOpt,
-            {
-                "parameters_milp": ParametersMilp.default(),
-            },
+            {},
         )
     ],
     "cp": [
+        (
+            CPSatMSRCPSPSolver,
+            {},
+        ),
         (
             CP_MS_MRCPSP_MZN,
-            {
-                "cp_solver_name": CPSolverName.CHUFFED,
-                "parameters_cp": ParametersCP.default(),
-                "exact_skills_need": False,
-            },
+            {},
         ),
         (
             CP_MS_MRCPSP_MZN_PREEMPTIVE,
             {
-                "cp_solver_name": CPSolverName.CHUFFED,
-                "parameters_cp": ParametersCP.default(),
-                "exact_skills_need": False,
                 "nb_preemptive": 5,
             },
         ),
     ],
-    "ls": [(LS_RCPSP_Solver, {"ls_solver": LS_SOLVER.SA, "nb_iteration_max": 20})],
-    "ga": [(GA_MSRCPSP_Solver, {"parameters_ga": ParametersAltGa.default_msrcpsp()})],
+    "ls": [(LS_RCPSP_Solver, {"nb_iteration_max": 20})],
+    "ga": [(GA_MSRCPSP_Solver, {})],
     "lns-scheduling": [
         (
             LargeNeighborhoodSearchScheduling,
             {
                 "nb_iteration_lns": 100,
                 "nb_iteration_no_improvement": 100,
-                "parameters_cp": ParametersCP.default(),
             },
         )
     ],

diff --git a/discrete_optimization/rcpsp_multiskill/solvers/ms_rcpsp_ga_solver.py b/discrete_optimization/rcpsp_multiskill/solvers/ms_rcpsp_ga_solver.py
@@ -11,9 +11,9 @@
 class GA_MSRCPSP_Solver(SolverDO):
     problem: RCPSPModel
 
-    def solve(
-        self, parameters_ga: ParametersAltGa = ParametersAltGa.default_msrcpsp(), **args
-    ):
+    def solve(self, parameters_ga: ParametersAltGa = None, **args):
+        if parameters_ga is None:
+            parameters_ga = ParametersAltGa.default_msrcpsp()
         ga_solver = AlternatingGa(
             problem=self.problem,
             encodings=parameters_ga.encodings,