WIP GA solver

discrete_optimization/generic_tools/ea/ga_tools.py

@@ -11,9 +11,28 @@
     DeapSelection,
     ObjectiveHandling,
 )
+from discrete_optimization.generic_tools.hyperparameters.hyperparameter import (
+    EnumHyperparameter,
+    FloatHyperparameter,
+    IntegerHyperparameter,
+)
+from discrete_optimization.generic_tools.hyperparameters.hyperparametrizable import (
+    Hyperparametrizable,
+)
+
 
+class ParametersGa(Hyperparametrizable):
+    hyperparameters = [
+        EnumHyperparameter(name="crossover", enum=DeapCrossover, default=None),
+        EnumHyperparameter(
+            name="selection", enum=DeapSelection, default=DeapSelection.SEL_TOURNAMENT
+        ),
+        IntegerHyperparameter(name="pop_size", low=1, high=1000, default=100),
+        FloatHyperparameter(name="mut_rate", low=0, high=0.9, default=0.1),
+        FloatHyperparameter(name="crossover_rate", low=0, high=1, default=0.9),
+        FloatHyperparameter(name="tournament_size", low=0, high=1, default=0.2),
+    ]
 
-class ParametersGa:
     def __init__(
         self,
         mutation: Union[Mutation, DeapMutation],

discrete_optimization/rcpsp/solver/rcpsp_ga_solver.py

@@ -10,29 +10,29 @@
     ParametersAltGa,
     ParametersGa,
 )
+from discrete_optimization.generic_tools.hyperparameters.hyperparameter import (
+    SubBrickKwargsHyperparameter,
+)
 from discrete_optimization.rcpsp.rcpsp_model import RCPSPModel
 from discrete_optimization.rcpsp.solver.rcpsp_solver import SolverRCPSP
 
 
 class GA_RCPSP_Solver(SolverRCPSP):
     problem: RCPSPModel
-    hyperparameters = Ga.copy_and_update_hyperparameters(
-        crossover=dict(
-            choices=[
-                DeapCrossover.CX_UNIFORM_PARTIALY_MATCHED,
-                DeapCrossover.CX_ORDERED,
-                DeapCrossover.CX_PARTIALY_MATCHED,
-            ]
+
+    hyperparameters = [
+        SubBrickKwargsHyperparameter(
+            name="parameters_ga_kwargs", subbrick_cls=ParametersGa
         )
-    )
-    # RCPSP needs permutation encoding, not all crossover are available.
+    ]
 
-    def solve(self, parameters_ga: Optional[ParametersGa] = None, **args):
+    def solve(self, parameters_ga: Optional[ParametersGa] = None, **kwargs):
         if parameters_ga is None:
             parameters_ga = ParametersGa.default_rcpsp()
-            args = self.complete_with_default_hyperparameters(args)
-        for key in args:
-            setattr(parameters_ga, key, args[key])
+        kwargs = self.complete_with_default_hyperparameters(kwargs)
+        if kwargs["parameters_ga_kwargs"] is not None:
+            for key in kwargs["parameters_ga_kwargs"]:
+                setattr(parameters_ga, key, kwargs["parameters_ga_kwargs"][key])
         ga_solver = Ga(
             problem=self.problem,
             encoding=parameters_ga.encoding,