Particle Swarm Optimization

Algorithm Parameters:

Parameter	Description
Analyzer	The operator used to analyze each generation.
Inertia	Inertia weight on a particle's movement (omega). Default: -0.2
InertiaUpdater	Updates the omega parameter.
MaxIterations	The maximum number of iterations which should be processed.
MutationProbability	The probability that the mutation operator is applied on a solution.
Mutator	The operator used to mutate solutions.
NeighborBestAttraction	Weight for pull towards the neighborhood best solution or global best solution in case of a totally connected topology (phi_g). Default: 3.7
ParticleCreator	Operator creates a new particle.
ParticleUpdater	Operator that updates a particle.
PersonalBestAttraction	Weight for particle's pull towards its personal best soution (phi_p). Default: -0.01
Population Size	The size of the population of solutions.
Seed	The random seed used to initialize the new pseudo random number generator.
Selector	The operator used to select solutions for reproduction.
SetSeedRandomly	True if the random seed should be set to a random value, otherwise false.
SwarmSize	Size of the particle swarm. Default: 10
SwarmUpdater	Encoding-specific parameter which is provided by the problem.
TopologyInitializer	Creates neighborhood description vectors.
TopologyUpdater	Updates the neighborhood description vectors.

Is there a sample/tutorial?

References:

• Kennedy, J. and Eberhart, R.C., 2001. Swarm Intelligence. Morgan Kaufmann. ISBN 1-55860-595-9.
• Pedersen, M.E.H., 2010. ​| Good parameters for particle swarm optimization. Technical Report HL1001 (Hvass Laboratories)