NiaOrg / NiaPy

		self.pmax, self.rp = pmax, rp

		if ukwargs: logger.info('Unused arguments: %s' % (ukwargs))

	def postSelection(self, pop, task, **kwargs):

		r"""Post selection operator.

		In this algorithm the post selection operator decrements the population at specific iterations/generations.

		Args:

			pop (numpy.ndarray[Individual]): Current population.

			task (Task): Optimization task.

			kwargs (Dict[str, Any]): Additional arguments.

		Returns:

			numpy.ndarray[Individual]: Changed current population.

		"""

		Gr = task.nFES // (self.pmax * len(pop)) + self.rp

		nNP = len(pop) // 2

		if task.Iters == Gr and len(pop) > 3: pop = objects2array([pop[i] if pop[i].f < pop[i + nNP].f else pop[i + nNP] for i in range(nNP)])

		return pop

def proportional(Lt_min, Lt_max, mu, x_f, avg, *args):

	r"""Proportional calculation of age of individual.

		self.rp, self.pmax = rp, pmax

		if ukwargs: logger.info('Unused arguments: %s' % (ukwargs))

	def postSelection(self, pop, task, **kwargs):

		r"""Post selection operator.

		Args:

			pop (numpy.ndarray[Individual]): Current population.

			task (Task): Optimization task.

		Returns:

			numpy.ndarray[Individual]: New population.

		"""

		Gr, nNP = task.nFES // (self.pmax * len(pop)) + self.rp, len(pop) // 2

		if task.Iters == Gr and len(pop) > 3: return objects2array([pop[i] if pop[i].f < pop[i + nNP].f else pop[i + nNP] for i in range(nNP)])

		return pop

class MultiStrategySelfAdaptiveDifferentialEvolution(SelfAdaptiveDifferentialEvolution):

	r"""Implementation of self-adaptive differential evolution algorithm with multiple mutation strategys.