blxalpha_crossover

x_i_new, of_i_new, fit_i_new, neof, report = blxalpha_crossover(of_function, parent_0, parent_1, n_dimensions, x_upper, x_lower, none_variable=None)

BLX alpha crossover operator.

Input variables

Name	Description	Type
of_function	Objective function	Py function (def)
parent_0	First parent	List
parent_1	Second parent	List
n_dimensions	Problem dimension	Integer
x_upper	Upper limit of the design variables	List
x_lower	Lower limit of the design variables	List
none_variable	None variable. Default is None. Use in objective function	None, List, Float, Dictionary, String or any

Output variables

Name	Description	Type
x_i_new	Update variables of the i agent	L'ist
of_i_new	Update objective function value of the i agent	Float
fit_i_new	Update fitness value of the i agent	Float
neof	New solution indicator. It is a Boolean value (1 to indicate a new solution)	Integer
report	Report about the crossover process	String

Example 1

# Import
from metapy_toolbox import blxalpha_crossover

# Data
#father1 = [1, 1, 1, 1, 1]
#father2 = [10, 10, 10, 10, 10]
# gere father 1 e father 2 com valores aleatórios
father1 = [1.5, 2.3, 1.8, 3.8, 2.4]
father2 = [2.3, 1.5, 1.5, 2.8, 4.4]
nDimensions = len(father1)
xUpper = [5, 5, 5, 5, 5]
xLower = [1, 1, 1, 1, 1]
noneVariable = None

# Objective function
def objFunction(x, _):
    """Example objective function"""
    x0 = x[0]
    x1 = x[1]
    of = x0 ** 2 + x1 ** 2
    return of

# Call function
xNew, ofNew, fitNew, neof, report = blxalpha_crossover(objFunction, father1, father2, nDimensions, xUpper, xLower, noneVariable)

# Output details
print('x new ', xNew)
print('of new ', ofNew)
print('fit new', fitNew)
print('number of evalutions objective function', neof)

x new  [1.0, 1.0, 1.0, 1.0, 1.0]
of new  2.0
fit new 0.3333333333333333
number of evalutions objective function 2

To check the movement report just apply the following instruction.

# Report details
arq = "report_example.txt"

# Writing report
with open(arq, "w") as file:
    file.write(report)

Open report_example.txt.

    Crossover operator - BLX-alpha
    current p0 = [1.5, 2.3, 1.8, 3.8, 2.4]
    current p1 = [2.3, 1.5, 1.5, 2.8, 4.4]
    Dimension 0: min_val = 1.5, max_val = 2.3, r_ij = 0.7999999999999998
    neighbor_a = 0.9591254809153907, neighbor_b = 2.840874519084609
    Dimension 1: min_val = 1.5, max_val = 2.3, r_ij = 0.7999999999999998
    neighbor_a = 0.7431857498245784, neighbor_b = 3.0568142501754214
    Dimension 2: min_val = 1.5, max_val = 1.8, r_ij = 0.30000000000000004
    neighbor_a = 1.473354543479718, neighbor_b = 1.826645456520282
    Dimension 3: min_val = 2.8, max_val = 3.8, r_ij = 1.0
    neighbor_a = 2.7797787480137583, neighbor_b = 3.8202212519862413
    Dimension 4: min_val = 2.4, max_val = 4.4, r_ij = 2.0000000000000004
    neighbor_a = 1.403318395158758, neighbor_b = 5.396681604841242
    offspring a = [1.0, 1.0, 1.0, 1.0, 1.0], of_a 2.0
    offspring b = [1.0, 1.0, 1.0, 1.0, 1.0], of_b 2.0
    update x = [1.0, 1.0, 1.0, 1.0, 1.0], of = 2.0, fit = 0.3333333333333333