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xegaPopulation  

Genetic Population Level Functions
View on CRAN: Click here


Download and install xegaPopulation package within the R console
Install from CRAN:
install.packages("xegaPopulation")

Install from Github:
library("remotes")
install_github("cran/xegaPopulation")

Install by package version:
library("remotes")
install_version("xegaPopulation", "1.0.0.0")



Attach the package and use:
library("xegaPopulation")
Maintained by
Andreas Geyer-Schulz
[Scholar Profile | Author Map]
First Published: 2024-03-04
Latest Update: 2024-03-04
Description:
This collection of gene representation-independent functions implements the population layer of extended evolutionary and genetic algorithms and its support. The population layer consists of functions for initializing, logging, observing, evaluating a population of genes, as well as of computing the next population. For parallel evaluation of a population of genes 4 execution models - named Sequential, MultiCore, FutureApply, and Cluster - are provided. They are implemented by configuring the lapply() function. The execution model FutureApply can be externally configured as recommended by Bengtsson (2021) <doi:10.32614/RJ-2021-048>. Configurable acceptance rules and cooling schedules (see Kirkpatrick, S., Gelatt, C. D. J, and Vecchi, M. P. (1983) <doi:10.1126/science.220.4598.671>, and Aarts, E., and Korst, J. (1989, ISBN:0-471-92146-7) offer simulated annealing or greedy randomized approximate search procedure elements. Adaptive crossover and mutation rates depending on population statistics generalize the approach of Stanhope, S. A. and Daida, J. M. (1996, ISBN:0-18-201-031-7).
How to cite:
Andreas Geyer-Schulz (2024). xegaPopulation: Genetic Population Level Functions. R package version 1.0.0.0, https://cran.r-project.org/web/packages/xegaPopulation. Accessed 21 Feb. 2025.
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