NiaOrg / NiaPy

		d.update({'strategies': self.strategies})

		return d

	def evolve(self, pop, xb, task, **kwargs):

		r"""Evolve population with the help multiple mutation strategies.

		Args:

			pop (numpy.ndarray): Current population.

			xb (numpy.ndarray): Current best individual.

			task (Task): Optimization task.

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

		Returns:

			numpy.ndarray: New population of individuals.

		"""

		return objects2array([self.CrossMutt(pop, i, xb, self.F, self.CR, self.Rand, task, self.itype, self.strategies) for i in range(len(pop))])

class DynNpMultiStrategyDifferentialEvolution(MultiStrategyDifferentialEvolution, DynNpDifferentialEvolution):

	r"""Implementation of Dynamic population size Differential evolution algorithm with dynamic population size that is defined by the quality of population.

		SelfAdaptiveDifferentialEvolution.setParameters(self, CrossMutt=kwargs.pop('CrossMutt', multiMutations), **kwargs)

		self.strategies = strategies

	def evolve(self, pop, xb, task, **kwargs):

		r"""Evolve population with the help multiple mutation strategies.

		Args:

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

			xb (Individual): Current best individual.

			task (Task): Optimization task.

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

		Returns:

			numpy.ndarray[Individual]: New population of individuals.

		"""

		return objects2array([self.CrossMutt(pop, i, xb, self.F, self.CR, self.Rand, task, self.itype, self.strategies) for i in range(len(pop))])

class DynNpMultiStrategySelfAdaptiveDifferentialEvolution(MultiStrategySelfAdaptiveDifferentialEvolution, DynNpSelfAdaptiveDifferentialEvolutionAlgorithm):

	r"""Implementation of Dynamic population size self-adaptive differential evolution algorithm with multiple mutation strategies.