Source code for macop.operators.crossovers.RandomSplitCrossover

"""Crossover implementation which generated new solution by randomly splitting best solution and current solution
"""
# main imports
import random
import sys
import pkgutil

# module imports
from .Crossover import Crossover
from ...utils.modules import load_class


[docs]class RandomSplitCrossover(Crossover): """Crossover implementation which generated new solution by randomly splitting best solution and current solution Attributes: kind: {KindOperator} -- specify the kind of operator """
[docs] def apply(self, _solution): """Create new solution based on best solution found and solution passed as parameter Args: _solution: {Solution} -- the solution to use for generating new solution Returns: {Solution} -- new generated solution """ size = _solution.size # copy data of solution firstData = _solution.data.copy() # get best solution from current algorithm secondData = self.algo.bestSolution.data.copy() splitIndex = random.randint(0, len(secondData)) if random.uniform(0, 1) > 0.5: firstData[splitIndex:(size - 1)] = firstData[splitIndex:(size - 1)] currentData = firstData else: secondData[splitIndex:(size - 1)] = firstData[splitIndex:(size - 1)] currentData = secondData # create solution of same kind with new data class_name = type(_solution).__name__ # dynamically load solution class if unknown if class_name not in sys.modules: load_class(class_name, globals()) return getattr(globals()['macop.solutions.' + class_name], class_name)(currentData, size)