piglot.optimisers.pso.GlobalBestPSOMod

class GlobalBestPSOMod(**kwargs)[source]

Bases: Missing_pyswarms

Methods

`compute_objective_function`	Evaluate particles using the objective function
`optimize`	Optimize the swarm for a number of iterations

Attributes

`name`
`package`

compute_objective_function(swarm, objective_func, pool=None, **kwargs)[source]

Evaluate particles using the objective function

This method evaluates each particle in the swarm according to the objective function passed.

If a pool is passed, then the evaluation of the particles is done in parallel using multiple processes.

Parameters

swarmpyswarms.backend.swarms.Swarm: a Swarm instance
objective_funcfunction: objective function to be evaluated
pool: multiprocessing.Pool: multiprocessing.Pool to be used for parallel particle evaluation
kwargsdict: arguments for the objective function

optimize(optimiser, objective_func, iters, n_processes=None, verbose=False, **kwargs)[source]

Optimize the swarm for a number of iterations

Performs the optimization to evaluate the objective function f for a number of iterations iter.

objective_funccallable: objective function to be evaluated
itersint: number of iterations
n_processesint: number of processes to use for parallel particle evaluation (default: None = no parallelization)
verbosebool: enable or disable the logs and progress bar (default: True = enable logs)
kwargsdict: arguments for the objective function