from .particle import Particle

class MOPSO():
    def __init__(self, n, t, w, c1, c2, a_max, surrogate=False):
        # Constants
        self.n = n # Number of particles
        self.t = t # Number of iterations
        self.w = w # Inertia (for exploration)
        self.c1 = c1 # Individual trust
        self.c2 = c2 # Social trust
        self.a_max = a_max # Archive size

        self.surrogate = surrogate # Using AI calculation

        self.particles = [] # Particles of the simulation
        # Fonctions objectifs
        # Limites variables de decision
    
    def iterate(self):
        nb_iter = 0
        if not self.surrogate:
            while nb_iter < self.t:
                nb_iter += 1
                # Selection of a leader
                # Updating velocity and positions
                # Checking boundaries
                # Evaluating particles
                # Update the archive
                # Checking for best positions
        else:
            while nb_iter < self.t:
                nb_iter += 1
                # Selection of a leader
                # Updating velocity and positions
                # Checking boundaries
                # Evaluating particles
                # Update the archive
                # Checking for best positions