metaheuristic_designer.encodings.special package

Submodules

metaheuristic_designer.encodings.special.PSO_encoding module

Encoding for Particle Swarm optimization that appends a velocity vector to the genotype.

class PSOEncoding(dimension: int, base_encoding: Encoding | None = None)[source]

Bases: ParameterExtendingEncoding

Encoding for Particle Swarm optimization that stores a velocity vector.

The genotype is split into the solution vector and a velocity vector of the same dimension. Both are used by the PSO operator.

Parameters:

  • dimension (int) – Number of decision variables.

  • base_encoding (Encoding, optional) – Encoding applied to the solution part. Defaults to DefaultEncoding.

metaheuristic_designer.encodings.special.self_adapting_ES_encoding module

Encoding for self-adapting Evolution Strategies that appends mutation strength parameters.

class SelfAdaptingESEncoding(dimension: int, single_sigma: bool = True, base_encoding: Encoding | None = None)[source]

Bases: ParameterExtendingEncoding

Encoding for self-adapting Evolution Strategies.

Appends one or more mutation strength values (F) to the solution vector. When single_sigma=True a single step size is shared by all dimensions; otherwise each dimension gets its own step size.

Parameters:

  • dimension (int) – Number of decision variables.

  • single_sigma (bool, optional) – If True (default), a single F value is added. If False, dimension values are added.

  • base_encoding (Encoding, optional) – Encoding applied to the solution part. Defaults to DefaultEncoding.

Module contents

Specialized encodings for specific algorithms (PSO, self-adapting ES).

class PSOEncoding(dimension: int, base_encoding: Encoding | None = None)[source]

Bases: ParameterExtendingEncoding

Encoding for Particle Swarm optimization that stores a velocity vector.

The genotype is split into the solution vector and a velocity vector of the same dimension. Both are used by the PSO operator.

Parameters:

  • dimension (int) – Number of decision variables.

  • base_encoding (Encoding, optional) – Encoding applied to the solution part. Defaults to DefaultEncoding.

class SelfAdaptingESEncoding(dimension: int, single_sigma: bool = True, base_encoding: Encoding | None = None)[source]

Bases: ParameterExtendingEncoding

Encoding for self-adapting Evolution Strategies.

Appends one or more mutation strength values (F) to the solution vector. When single_sigma=True a single step size is shared by all dimensions; otherwise each dimension gets its own step size.

Parameters:

  • dimension (int) – Number of decision variables.

  • single_sigma (bool, optional) – If True (default), a single F value is added. If False, dimension values are added.

  • base_encoding (Encoding, optional) – Encoding applied to the solution part. Defaults to DefaultEncoding.