pygsti.optimize.fmin_particle_swarm

pygsti.optimize.fmin_particle_swarm(f, x0, err_crit, iter_max, popsize=100, c1=2, c2=2)

A simple implementation of the Particle Swarm Optimization Algorithm. Pradeep Gowda 2009-03-16

Parameters:
  • f (function) – The function to minimize.
  • x0 (numpy array) – The starting point (argument to fn).
  • err_crit (float) – Critical error (i.e. tolerance). Stops when error < err_crit.
  • iter_max (int) – Maximum iterations.
  • popsize (int, optional) – Population size. Larger populations are better at finding the global optimum but make the algorithm take longer to run.
  • c1 (float, optional) – Coefficient describing a particle’s affinity for it’s (local) maximum.
  • c2 (float, optional) – Coefficient describing a particle’s affinity for the best maximum any particle has seen (the current global max).
Returns:

Includes members ‘x’, ‘fun’, ‘success’, and ‘message’.

Return type:

scipy.optimize.Result object