"""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
# import all available solutions
for loader, module_name, is_pkg in pkgutil.walk_packages(
path=['macop/solutions'], prefix='macop.solutions.'):
_module = loader.find_module(module_name).load_module(module_name)
globals()[module_name] = _module
[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__
return getattr(globals()['macop.solutions.' + class_name],
class_name)(currentData, size)