saealib.PSO¶

class saealib.PSO(w=0.7, c1=1.5, c2=1.5, v_max=None)[source]¶

Bases: Algorithm

Particle Swarm Optimization (PSO) for single-objective problems.

The global best (leader) is selected from the personal bests of all particles using ctx.comparator, so the ranking adapts automatically to any single-objective Comparator.

Multi-objective PSO (MOPSO) requires a dedicated subclass with a separate Pareto archive for leader selection.

Parameters:

w (float)
c1 (float)
c2 (float)
v_max (float | None)

w¶

Inertia weight.

Type:: float

c1¶

Cognitive coefficient (personal best attraction).

Type:: float

c2¶

Social coefficient (global best attraction).

Type:: float

v_max¶

Maximum velocity magnitude per dimension. None disables clamping.

Type:: float or None

Methods

`__init__`	Initialize PSO.
`ask`	Update particle velocities and positions.
`create_pareto_archive`	Create a ParetoArchive with the correct direction for the problem.
`get_required_attrs`	Return PSO-specific attributes required by the Population.
`tell`	Update the population and personal bests from evaluated offspring.

Method Details

PSO.__init__(w=0.7, c1=1.5, c2=1.5, v_max=None)[source]¶

Initialize PSO.

Parameters:

w (float, optional) – Inertia weight. Defaults to 0.7.
c1 (float, optional) – Cognitive coefficient. Defaults to 1.5.
c2 (float, optional) – Social coefficient. Defaults to 1.5.
v_max (float or None, optional) – Maximum velocity per dimension. Defaults to None (no clamping).

PSO.ask(ctx, provider, n_offspring=None)[source]¶

Update particle velocities and positions.

Parameters:

ctx (OptimizationContext) – Current optimization context.
provider (ComponentProvider) – Component provider.
n_offspring (int or None, optional) – Ignored; output count equals population size.

Returns:

Candidates with updated x and velocity.

Return type:

Population

PSO.create_pareto_archive(attrs, init_capacity, problem)¶

Create a ParetoArchive with the correct direction for the problem.

Parameters:

attrs (list[PopulationAttribute])
init_capacity (int)
problem (Problem)

Return type:

ParetoArchive

PSO.get_required_attrs(problem)[source]¶

Return PSO-specific attributes required by the Population.

Parameters:: problem (Problem) – The Problem object being referenced.
Returns:: velocity, pbest_x, pbest_f, and pbest_cv attributes.
Return type:: list[PopulationAttribute]

PSO.tell(ctx, provider, offspring)[source]¶

Update the population and personal bests from evaluated offspring.

Parameters:

ctx (OptimizationContext) – Current optimization context.
provider (ComponentProvider) – Component provider.
offspring (Population) – Evaluated offspring population.

Return type:

None