How do PSO parameters affect optimization results?

How do PSO parameters affect optimization results?

The parameters in Particle Swarm Optimization (PSO), like inertia weight and cognitive/social coefficients, significantly influence the convergence speed and solution quality.

Can you explain what inertia weight does?

Inertia weight controls the influence of a particle's previous velocity on its current velocity, helping to balance exploration and exploitation.

What happens if the inertia weight is too high?

If the inertia weight is too high, particles may overshoot optimal solutions, leading to slower convergence and potential divergence.

Are there recommended values for the cognitive and social coefficients?

Typically, cognitive and social coefficients are set between 1.5 and 2.0, but tuning them based on the specific problem can yield better results.