metaheuristic_designer.simple.differential_evolution module#

Ready-to-run Differential Evolution wrappers.

differential_evolution_binary(objfunc, population_size=100, F=0.8, Cr=0.9, de_operator_name='de/rand/1', encoding=None, rng=None, **kwargs)[source]#

Differential Evolution for binary-encoded vectors.

Return type:

Algorithm

Parameters:
objfuncObjectiveFunc

The objective function to optimize.

population_sizeint, optional

Population size (default 100).

Ffloat, optional

Mutation scale factor (default 0.8).

Crfloat, optional

Crossover probability (default 0.9).

de_operator_namestr, optional

DE variant (default "de/rand/1").

encodingEncoding, optional

Encoding; defaults to SigmoidEncoding.

rngRNGLike, optional

Random seed or generator.

**kwargs

Forwarded to Algorithm.

Parameters:

  • objfunc (ObjectiveFunc)

  • population_size (int)

  • F (float)

  • Cr (float)

  • de_operator_name (str)

  • encoding (Encoding | None)

  • rng (int | Generator | None)

differential_evolution_discrete(objfunc, population_size=100, F=0.8, Cr=0.9, de_operator_name='de/rand/1', encoding=None, rng=None, **kwargs)[source]#

Differential Evolution for integer-coded vectors.

Return type:

Algorithm

Parameters:
objfuncObjectiveFunc

The objective function to optimize.

population_sizeint, optional

Population size (default 100).

Ffloat, optional

Mutation scale factor (default 0.8).

Crfloat, optional

Crossover probability (default 0.9).

de_operator_namestr, optional

DE variant (default "de/rand/1").

encodingEncoding, optional

Encoding; defaults to TypeCastEncoding (float → int).

rngRNGLike, optional

Random seed or generator.

**kwargs

Forwarded to Algorithm.

Parameters:

  • objfunc (ObjectiveFunc)

  • population_size (int)

  • F (float)

  • Cr (float)

  • de_operator_name (str)

  • encoding (Encoding | None)

  • rng (int | Generator | None)

differential_evolution_real(objfunc, population_size=100, F=0.8, Cr=0.9, de_operator_name='de/rand/1', encoding=None, rng=None, **kwargs)[source]#

Differential Evolution for real-coded vectors.

Return type:

Algorithm

Parameters:
objfuncObjectiveFunc

The objective function to optimizes.

population_sizeint, optional

Population size (default 100).

Ffloat, optional

Mutation scale factor (default 0.8).

Crfloat, optional

Crossover probability (default 0.9).

de_operator_namestr, optional

DE variant (default "de/rand/1").

encodingEncoding, optional

Encoding applied to the genotype.

rngRNGLike, optional

Random seed or generator.

**kwargs

Forwarded to Algorithm.

Parameters:

  • objfunc (ObjectiveFunc)

  • population_size (int)

  • F (float)

  • Cr (float)

  • de_operator_name (str)

  • encoding (Encoding | None)

  • rng (int | Generator | None)