Example #1
0
	def realCrossover( self, parent1, parent2, crossPoint ):
		child1 = Individual(
			chromosome = numpy.append( parent1[:crossPoint], parent2[crossPoint:] ),
			function = self.function
		)
		child2 = Individual(
			chromosome = numpy.append( parent2[:crossPoint], parent1[crossPoint:] ),
			function = self.function
		)

		return ( child1, child2 )
Example #2
0
	def lcCrossover( self, parent1, parent2 ):
		alpha = numpy.random.uniform()
		c1 = alpha * parent1 + ( 1 - alpha ) * parent2
		c2 = ( 1 - alpha ) * parent1 + alpha * parent2
		child1 = Individual(
			chromosome = c1,
			function = self.function
		)
		child2 = Individual(
			chromosome = c2,
			function = self.function
		)

		return ( child1, child2 )
Example #3
0
	def realMutation( self, chromosome ):
		pos = randrange( 0, self.dimensionsLength )
		lim_min, lim_max = self.limits[0], self.limits[1]
		sigma = (lim_max - lim_min) / 100
		new_chrom = numpy.array( chromosome[:] )
		new_chrom[pos] += numpy.random.randn() * sigma
		if new_chrom[pos] > lim_max or new_chrom[pos] < lim_min:
			return Individual(chromosome = chromosome, function = self.function)
		
		child = Individual(
			chromosome = new_chrom,
			function = self.function
		)

		return child
Example #4
0
	def mutation( self, chromosome ):
		position = randint( 0, self.chromosomeLength )
		child = Individual(
			chromosome = chromosome ^ 2 ** position,
			function = self.function
		)

		return child
Example #5
0
	def crossover( self, parent1, parent2, crossPoint ):
		mask1 = sum( [2 ** i for i in range( crossPoint )] )
		mask2 = sum( [2 ** i for i in range( crossPoint, self.chromosomeLength )] )
		crossParent11 = parent1 & mask1
		crossParent12 = parent1 & mask2
		crossParent21 = parent2 & mask1
		crossParent22 = parent2 & mask2
		child1 = Individual(
			chromosome = crossParent11 | crossParent22,
			function = self.function
		)
		child2 = Individual(
			chromosome = crossParent21 | crossParent12,
			function = self.function
		)

		return ( child1, child2 )
Example #6
0
	def createPopulation( self ):
		self.population = [Individual(
			chromosome = randint( 0, sum( [2 ** i for i in range( self.chromosomeLength )] ) ),
			function = self.function
		) for _ in range( self.populationLength )]
Example #7
0
	def dcCreatePopulation( self ):
		minLim, maxLim = self.limits[0], self.limits[1]
		self.population = numpy.array( [Individual(
			chromosome = numpy.random.uniform( minLim, maxLim, self.dimensionsLength ),
			function = self.function
		) for _ in range( self.populationLength )] )