recUnifCrossover

Produces two child individuals. The i-th gene is from parent1 with probability
<code>p</code> and from parent2 with probability <code>1-p</code>.

Framework for building evolutionary algorithms for both single- and multi-objective continuous or discrete optimization problems. A set of predefined evolutionary building blocks and operators is included. Moreover, the user can easily set up custom objective functions, operators, building blocks and representations sticking to few conventions. The package allows both a black-box approach for standard tasks (plug-and-play style) and a much more flexible white-box approach where the evolutionary cycle is written by hand.

Jakob Bossek

Evolutionary Computation in R

Michael H. Buselli

Wessel Dankers

Carlos M. Fonseca

Manuel Lopez-Ibanez

Luis Paquete

Joshua Knowles

Eckart Zitzler

Olaf Mersmann

recUnifCrossover function

<dl><dt>inds</dt>
<dd>[<code>list</code>] 
Parents, i.e., list of exactly two numeric or binary vectors of equal length.</dd>
<dt>p</dt>
<dd>[<code>numeric(1)</code>] 
Probability to select gene from parent1.</dd></dl>

Arguments

Uniform crossover recombinator. — recUnifCrossover

<dl>

<dt>inds</dt>
<dd>[<code>list</code>] 
Parents, i.e., list of exactly two numeric or binary vectors of equal length.</dd>


<dt>p</dt>
<dd>[<code>numeric(1)</code>] 
Probability to select gene from parent1.</dd>

</dl>

State of Data and AI Literacy Report 2025

recUnifCrossover: Uniform crossover recombinator.

Description

Usage

Value

Arguments

See Also