We need to have the following PSO implementation considerations:
- PSO stores an agent's best position in a considerable and relevant timeline along with the global best position for the swarm. With this, the agent with a maximum fitness score has an influence on the overall behavior of the swarm and the convergence is fast.
- PSO is a simple algorithm to implement since the mathematical equations for velocity and position are easy to implement due to inherent simplicity.
- PSO can adapt to the changes in environment very efficiently by adjusting the velocity and positions of the members quickly through each iteration.
