selectForSurvival

[<code>ecr_opt_state</code>]
Optimization state.

opt.state

population

[<code>ecr_control</code>]
ECR control object generated via <code><a rd-options="" href="/link/setupECRControl?package=ecr&version=1.0" data-mini-rdoc="ecr::setupECRControl">setupECRControl</a></code>.

control

[<code>integer(1L)</code>]
Number of offspring to select for survival.

n.select


Given the current optimization state this function selects a subset of individuals
which should survive and form the next generation.


Provides a powerful framework for evolutionary
computing in R. The user can easily construct powerful evolutionary algorithms
for tackling both single- and multi-objective problems by plugging in different
predefined evolutionary building blocks, e. g., operators for mutation,
recombination and selection with just a few lines of code. Your problem
cannot be easily solved with a standard EA which works on real-valued vectors,
permutations or binary strings? No problem, 'ecr' has been developed with that in
mind. Extending the framework with own operators is also possible. Additionally
there are various comfort functions, like monitoring, logging and more.

Jakob Bossek

Evolutionary Computing in R

selectForSurvival function

[<code>ecr_control</code>]
ECR control object generated via <code><a rd-options='' href='setupECRControl'>setupECRControl</a></code>.

selectForSurvival: Generate mating pool.

Description

Usage

Arguments

Value