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Machine Coded Genetic Algorithms for Real-Valued Optimization Problems

0packages depend
4Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Machine coded genetic algorithm (MCGA) is a fast tool for real-valued optimization problems. It uses the byte representation of variables rather than real-values. It performs the classical crossover operations (uniform) on these byte representations. Mutation operator is also similar to classical mutation operator, which is to say, it changes a randomly selected byte value of a chromosome by +1 or -1 with probability 1/2. In MCGAs there is no need for encoding-decoding process and the classical operators are directly applicable on real-values. It is fast and can handle a wide range of a search space with high precision. Using a 256-unary alphabet is the main disadvantage of this algorithm but a moderate size population is convenient for many problems. Package also includes multi_mcga function for multi objective optimization problems. This function sorts the chromosomes using their ranks calculated from the non-dominated sorting algorithm.

Install

Health

CRAN checks
13OK
Slowest check: 2.8 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-04-22
  • ERROR13 OK, 1 ERROR2026-04-18
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 3.0.9
READMENoVignettesNoNEWSNoCitation fileYes · cites a publicationWebsitenot declared in DESCRIPTION
Help pages
36 (1 internal)includes a package overview page
Examples that run
94%33 run in a plain check · 2 never run
Exported functions with examples
100%
Documented parameters
not tracked
Return-value docs
not tracked
Help pages citing references
31%

Downloads

4K
CRAN downloads in the past year
Rank #8,725 · ~11/day · ~332/mo
Daily download trend is not available in this view yet.
39330 days
1.1K90 days
4K1 year
Compare downloads with other packages →
Also on381 r2u2 autocran146 c2d4u

Dependencies

Declared dependencies
3 external dependencies (excludes base and recommended)

Installing mcga adds 7 packages (4 with compiled code, 8.6 MB of source tarballs). Heaviest: GA 4.8 MB, Rcpp 1.8 MB, RcppArmadillo 1.0 MB.

Depends (1)
Imports (1)
LinkingTo (1)
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (1)
Author, Maintainer since 1.0 (2010)
Listed in earlier versions (1)
Satman
no longer listed · 3.0.9
Releases (19)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 3.0.9Latest
    record
    2025-12-10 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • 3.0.7
    record
    2023-11-27 · diff ↗
  • 3.0.6
    record
    2023-08-20 · diff ↗
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • 3.0.3
    record
    2018-05-13 · diff ↗
  • R
    R 3.5.0 released · 2018-04-23
  • R
    R 3.4.0 released · 2017-04-21
  • 3.0.1
    record
    2016-05-12 · diff ↗
  • R
    R 3.3.0 released · 2016-05-03
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Package metadata

First published
2010-12-13
Total releases
19 / 16 yrs
License
GPL (>= 2) OSI
Download size
24 KB

Cite

Cite this package

Run in R for the authors' entry:

citation("mcga")

The package provides a citation file, so citation() returns the authors' own entry.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for mcga version 3.0.9 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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