describes the condition that triggers the transition. The
process for implementing the global version of the PSO
is as follows:
Step 1 Initialize a population (array) of particles
with random positions and velocities in d
dimensions in the problem space.
Step 2 For each particle, evaluate the desired optimization
fitness function in j variables.
Step 3 Compare the particle fitness evaluation
of each particle with its local_best. If current
value is better than the local_best,
set the local_best value to the current
value and the local_best location equal to
the current location in the j-dimensional
space.
Step 4 Compare the fitness evaluation with the
overall previous best of the population. If
the current value is better than the global_
best, reset the global_best to the current
array index and value of the particle.