metaheuristic_designer.simple.evolution_strategy module#
Ready-to-run Evolution Strategy wrappers.
- evolution_strategy_binary(objfunc, mutated_bits=1, population_size=100, offspring_size=500, elitist=False, encoding=None, rng=None, **kwargs)[source]#
Evolution Strategy for binary-coded vectors.
- Return type:
- Parameters:
- objfuncObjectiveFunc
The objective function to optimize.
- mutated_bitsint, optional
Number of bits flipped per mutation (default 1).
- population_sizeint, optional
Population size (default 100).
- offspring_sizeint, optional
Number of offspring per generation (default 500).
- elitistbool, optional
If
True, use (μ+λ) selection; otherwise (μ,λ).- encodingEncoding, optional
Encoding; defaults to
TypeCastEncoding(int → bool).- rngRNGLike, optional
Random seed or generator.
- **kwargs
Forwarded to
Algorithm.
- Parameters:
objfunc (ObjectiveFunc)
mutated_bits (int)
population_size (int)
offspring_size (int)
elitist (bool)
encoding (Encoding | None)
rng (int | Generator | None)
- evolution_strategy_permutation(objfunc, swapped_positions=2, population_size=100, offspring_size=500, elitist=False, encoding=None, rng=None, **kwargs)[source]#
Evolution Strategy for permutation-coded vectors.
- Return type:
- Parameters:
- objfuncObjectiveFunc
The objective function to optimize.
- swapped_positionsint, optional
Number of positions swapped per mutation (default 2).
- population_sizeint, optional
Population size (default 100).
- offspring_sizeint, optional
Number of offspring per generation (default 500).
- elitistbool, optional
If
True, use (μ+λ) selection; otherwise (μ,λ).- encodingEncoding, optional
Encoding applied to the genotype.
- rngRNGLike, optional
Random seed or generator.
- **kwargs
Forwarded to
Algorithm.
- Parameters:
objfunc (ObjectiveFunc)
swapped_positions (int)
population_size (int)
offspring_size (int)
elitist (bool)
encoding (Encoding | None)
rng (int | Generator | None)
- evolution_strategy_discrete(objfunc, resampled_components=1, population_size=100, offspring_size=500, elitist=False, encoding=None, rng=None, **kwargs)[source]#
Evolution Strategy for integer-coded vectors.
- Return type:
- Parameters:
- objfuncObjectiveFunc
The objective function to optimize.
- resampled_componentsint, optional
Number of components resampled per mutation (default 1).
- population_sizeint, optional
Population size (default 100).
- offspring_sizeint, optional
Number of offspring per generation (default 500).
- elitistbool, optional
If
True, use (μ+λ) selection; otherwise (μ,λ).- encodingEncoding, optional
Encoding applied to the genotype.
- rngRNGLike, optional
Random seed or generator.
- **kwargs
Forwarded to
Algorithm.
- Parameters:
objfunc (ObjectiveFunc)
resampled_components (int)
population_size (int)
offspring_size (int)
elitist (bool)
encoding (Encoding | None)
rng (int | Generator | None)
- evolution_strategy_real(objfunc, mutation_strength=0.01, mutated_components=1, population_size=100, offspring_size=500, elitist=False, encoding=None, rng=None, **kwargs)[source]#
Evolution Strategy for integer-coded vectors.
- Return type:
- Parameters:
- objfuncObjectiveFunc
The objective function to optimize.
- resampled_componentsint, optional
Number of components resampled per mutation (default 1).
- population_sizeint, optional
Population size (default 100).
- offspring_sizeint, optional
Number of offspring per generation (default 500).
- elitistbool, optional
If
True, use (μ+λ) selection; otherwise (μ,λ).- encodingEncoding, optional
Encoding applied to the genotype.
- rngRNGLike, optional
Random seed or generator.
- **kwargs
Forwarded to
Algorithm.
- Parameters:
objfunc (ObjectiveFunc)
mutation_strength (float)
mutated_components (int)
population_size (int)
offspring_size (int)
elitist (bool)
encoding (Encoding | None)
rng (int | Generator | None)