Introduction à l'implémentation Python de l'algorithme d'optimisation d'essaim de particules (PSO)

For Iter in range(max_iter): For i in range(N): a.Compute new velocity of ith particle swarm.velocity= w*swarm.velocity+ r1*c1*(swarm.bestPos-swarm.position)+ r2*c2*(best_pos_swarm-swarm.position) b.If velocity is not in range[minx,max]then clip it if swarm.velocity<minx: swarm.velocity=minx elif swarm.velocity[k]>maxx: swarm.velocity[k]=maxx c.Compute new position of ith particle using its new velocity swarm.position+=swarm.velocity d.Update new best of this particle and new best of Swarm if swarm.fitness<swarm.bestFitness: swarm.bestFitness=swarm.fitness swarm.bestPos=swarm.position if swarm.fitness<best_fitness_swarm best_fitness_swarm=swarm.fitness best_pos_swarm=swarm.position End-for End-for Step 4:Return best particle of Swarm