crowding_distance.py

#!/usr/bin/env python
# encoding: utf-8
import numpy as np


def crowding_distance(pop_obj, front_no):
    """
    The crowding distance of each Pareto front
    :param pop_obj: objective vectors
    :param front_no: front numbers
    :return: crowding distance
    """
    n, M = np.shape(pop_obj)
    crowd_dis = np.zeros(n)
    front = np.unique(front_no)
    Fronts = front[front != np.inf]
    for f in range(len(Fronts)):
        Front = np.array([k for k in range(len(front_no)) if front_no[k] == Fronts[f]])
        Fmax = pop_obj[Front, :].max(0)
        Fmin = pop_obj[Front, :].min(0)
        for i in range(M):
            rank = np.argsort(pop_obj[Front, i])
            crowd_dis[Front[rank[0]]] = np.inf
            crowd_dis[Front[rank[-1]]] = np.inf
            for j in range(1, len(Front) - 1):
                crowd_dis[Front[rank[j]]] = crowd_dis[Front[rank[j]]] + (pop_obj[(Front[rank[j + 1]], i)] - pop_obj[
                    (Front[rank[j - 1]], i)]) / (Fmax[i] - Fmin[i])
    return crowd_dis