Source code for moead_framework.aggregation.weighted_sum

from .functions import AggregationFunction


class WeightedSum(AggregationFunction):
    """
    Weighted Sum aggregation function
    """
    def is_better(self, old_value, new_value):
        """
        Allow to compare 2 aggregations values for the weighted-sum function in a minimization context.

        :param old_value: {float} old aggregation value
        :param new_value: {float} new aggregation value
        :return: {boolean} True if new_value is better than old_value.
        """
        super().is_better(old_value, new_value)
        return new_value < old_value

    def run(self, solution, number_of_objective, weights, sub_problem, z):
        """
        Compute the WeightedSum value.

        :param solution: {:class:`~moead_framework.solution.one_dimension_solution.OneDimensionSolution`}
        :param number_of_objective: {integer} number of objective
        :param weights: {list<list<integer>>} List of weight vectors
        :param sub_problem: {integer} index of the sub-problem / weight vector
        :param z: {list<float>} coordinates of the reference point Z*
        :return: {float} the aggregation value of the solution for the weight vector: weights[sub-problem]
        """
        super().run(solution, number_of_objective, weights, sub_problem, z)

        res = 0
        for i in range(number_of_objective):
            res += solution.F[i] * weights[sub_problem][i]
        return res