laplace_crossover

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

This function performs the laplace crossover operator. Two new points are generated from the two parent points (offspring).

Input variables

Name	Description	Type
of_function	Objective function	Py function (def)
parent_0	Current design variables of the first parent	List
parent_1	Current design variables of the second parent	List
mu	location parameter	Float
sigma	scale parameter	Float
n_dimensions	Problem dimension	Integer
x_lower	Lower limit of the design variables	List
x_upper	Upper 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

from metapy_toolbox import laplace_crossover

# Data
father1 = [3.1, 1.7, 1.2, 3.4, 4.7]
father2 = [4.2, 1.6, 3.3, 3.0, 3.7]
mu = 0.75
sigma = 0.25
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 = laplace_crossover(objFunction, father1, father2, mu, sigma, 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  [7.548562129830823, 9.716816253769316, 9.401494014953634, 10.0, 10.0]
of new  46.66687239855378
fit new 0.02097893043283327
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 - Arithmetic crossover
    current p0 = [2.0, 1.5, 1.6, 3.7, 3.4]
    current p1 = [2.6, 4.9, 1.9, 3.2, 2.9]
    neighbor_a = 2.099209543646729, neighbor_b = 2.500790456353271
    neighbor_a = 3.1226423497299867, neighbor_b = 3.2773576502700137
    neighbor_a = 1.8636934930092481, neighbor_b = 1.6363065069907519
    neighbor_a = 3.5158093202927043, neighbor_b = 3.384190679707296
    neighbor_a = 3.0300633766390743, neighbor_b = 3.2699366233609255
    offspring a = [2.099209543646729, 3.1226423497299867, 2.0, 3.5158093202927043, 3.0300633766390743], of_a = 14.157575952464722
    offspring b = [2.500790456353271, 3.2773576502700137, 2.0, 3.384190679707296, 3.2699366233609255], of_b = 16.995026074370987
    update pos = [2.099209543646729, 3.1226423497299867, 2.0, 3.5158093202927043, 3.0300633766390743], of = 14.157575952464722, fit = 0.06597360970752011