sbx_crossover: Performs sbx (simulated binary) crossover operation on a pair...

In mcga: Machine Coded Genetic Algorithms for Real-Valued Optimization Problems

Performs sbx (simulated binary) crossover operation on a pair of two selected parent candidate solutions

Description

This function is not called directly but is given as a parameter in GA::ga function. In GA::ga, if the parameter crossover= is set to sbx_crossover than the sbx crossover operator is applied in the genetic search. sbx_crossover mimics the classical single-point crossover operator in binary genetic algorithms.

Usage

sbx_crossover(object, parents, ...)

Arguments

object	A GA::ga object
parents	Indices of the selected parents
...	Additional arguments to be passed to the function

Value

List of two generated offspring

Author(s)

Mehmet Hakan Satman - [e-mail]

References

Deb, Kalyanmoy, and Ram Bhushan Agrawal. "Simulated binary crossover for continuous search space." Complex systems 9.2 (1995): 115-148.

Examples

f <- function(x){ 
  return(-sum( (x-5)^2 ) )
}
myga <- ga(type="real-valued", fitness = f, popSize = 100, maxiter = 100, 
           min = rep(-50,5), max = rep(50,5), crossover = sbx_crossover)
print(myga@solution)

mcga documentation built on Nov. 27, 2023, 5:12 p.m.