uniformcrossover: Uniform crossover to produce offsprings
In changepointGA: Changepoint Detection via Modified Genetic Algorithm

uniformcrossover

R Documentation

Uniform crossover to produce offsprings

Description

In uniform crossover, typically, each bit is chosen from either parent with equal probability. Other mixing ratios are sometimes used, resulting in offspring which inherit more genetic information from one parent than the other. In a uniform crossover, we don’t divide the chromosome into segments, rather we treat each gene separately. In this, we essentially flip a coin for each chromosome to decide whether or not it will be included in the off-spring. If model order selection is requested, each child's model order has the equal probability (0.5) from dad and mom.

Usage

uniformcrossover(mom, dad, prange, minDist, lmax, N)

Arguments

`mom`	Among two selected individuals, `mom` represents the selected chromosome representation with lower fitness function value.
`dad`	Among two selected individuals, `dad` represents the selected chromosome representation with larger fitness function value.
`prange`	Default value is `NULL` for only changepoint detection. If `prange` is specified as a list object, which contains the range of each model order parameters for order selection (integers). The number of order parameters must be equal to the length of `prange`.
`minDist`	The required minimum distance between two adjacent changepoints.
`lmax`	The user specified maximum number of changepoints, by default, as `N/2 - 1`.
`N`	The length of time series.