boundedSBXover {nsga2R}

Bounded Simulated Binary Crossover Operator

Description

The simulated binary crossover operator is a real-parameter genetic operator. It simulates the working principal of the single-point crossover operator on binary strings.

Usage

boundedSBXover(parent_chromosome, lowerBounds, upperBounds, cprob, mu)

Arguments

parent_chromosome

Mating pool with decision variables

lowerBounds

Lower bounds of each decision variable

upperBounds

Upper bounds of each decision variable

cprob

Crossover probability

mu

Crossover distribution index, it can be any nonnegative real number

Value

Return the offspring population with decision variables

Author(s)

Ching-Shih (Vince) Tsou [e-mail]

References

Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. (2002), " A fast and elitist multiobjective genetic algorithm: NSGA-II", IEEE Transactions on Evolutionary Computation, 6(2), 182-197.

Examples

set.seed(1234)
lowerBounds <- rep(0,30)
upperBounds <- rep(1,30)
cprob <- 0.7
XoverDistIdx <- 20
matingPool <- matrix(runif(1200, 0, 1), nrow=40, ncol=30)
childAfterX <- boundedSBXover(matingPool,lowerBounds,upperBounds,cprob,XoverDistIdx)
childAfterX