Source code for surrogate.selection.selTournamentDCD

# Copyright 2016 Quan Pan
# 
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# 
#    http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# Author: Quan Pan <quanpan302@hotmail.com>
# License: Apache License, Version 2.0
# Create: 2016-12-02

import random

def selTournamentDCD(individuals, k):
    """Tournament selection based on dominance (D) between two individuals, if
    the two individuals do not interdominate the selection is made
    based on crowding distance (CD). The *individuals* sequence length has to
    be a multiple of 4. Starting from the beginning of the selected
    individuals, two consecutive individuals will be different (assuming all
    individuals in the input list are unique). Each individual from the input
    list won't be selected more than twice.

    This selection requires the individuals to have a :attr:`crowding_dist`
    attribute, which can be set by the :func:`assignCrowdingDist` function.

    :param individuals: A list of individuals to select from.
    :param k: The number of individuals to select.
    :returns: A list of selected individuals.
    """

    def tourn(ind1, ind2):
        if ind1.fitness.dominates(ind2.fitness):
            return ind1
        elif ind2.fitness.dominates(ind1.fitness):
            return ind2

        if ind1.fitness.crowding_dist < ind2.fitness.crowding_dist:
            return ind2
        elif ind1.fitness.crowding_dist > ind2.fitness.crowding_dist:
            return ind1

        if random.random() <= 0.5:
            return ind1
        return ind2

    individuals_1 = random.sample(individuals, len(individuals))
    individuals_2 = random.sample(individuals, len(individuals))

    chosen = []
    for i in xrange(0, k, 4):
        chosen.append(tourn(individuals_1[i], individuals_1[i + 1]))
        chosen.append(tourn(individuals_1[i + 2], individuals_1[i + 3]))
        chosen.append(tourn(individuals_2[i], individuals_2[i + 1]))
        chosen.append(tourn(individuals_2[i + 2], individuals_2[i + 3]))

    return chosen