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mcga
View on CRAN: Click
here
Download and install mcga package within the R console
Install from CRAN:
install.packages("mcga")
Install from Github:
library("remotes")
install_github("cran/mcga")
Install by package version:
library("remotes")
install_version("mcga", "3.0.7")
Attach the package and use:
library("mcga")
Maintained by
Mehmet Hakan Satman
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.mcga . mcga citation info . mcga results . mcga.pdf . mcga_3.0.7.tar.gz . mcga_3.0.7.zip . mcga_3.0.7.zip . mcga_3.0.7.zip . mcga_3.0.7.tgz . mcga_3.0.7.tgz . mcga_3.0.7.tgz . mcga_3.0.7.tgz . mcga_3.0.7.tgz . mcga_3.0.7.tgz . mcga archive . https://CRAN.R-project.org/package=mcga .
First Published: 2010-12-13
Latest Update: 2023-08-20
Description:
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.
How to cite:
Mehmet Hakan Satman (2010). mcga: Machine Coded Genetic Algorithms for Real-Valued Optimization Problems. R package version 3.0.7, https://cran.r-project.org/web/packages/mcga. Accessed 14 Mar. 2025.
Previous versions and publish date:
1.0 (2010-12-13 15:13), 1.1 (2010-12-23 12:28), 1.2.1 (2011-01-11 20:06), 1.2 (2011-01-11 12:28), 2.0.1 (2011-06-25 20:49), 2.0.2 (2011-10-17 20:41), 2.0.3 (2012-01-06 21:56), 2.0.4 (2012-01-06 22:02), 2.0.5 (2012-01-09 07:04), 2.0.6 (2012-10-31 10:31), 2.0.7 (2013-04-04 20:58), 2.0.9 (2014-03-25 12:23), 2.0 (2011-06-21 15:03), 3.0.1 (2016-05-12 16:24), 3.0.3 (2018-05-13 22:30), 3.0.6 (2023-08-20 13:12), 3.0 (2016-03-25 00:05)
Other packages that cited mcga R package
View mcga citation profile
Other R packages that mcga depends,
imports, suggests or enhances
Complete documentation for mcga
Functions, R codes and Examples using
the mcga R package
Some associated functions: ByteCodeMutation . ByteCodeMutationUsingDoubles . ByteCodeMutationUsingDoublesRandom . ByteVectorToDoubles . BytesToDouble . DoubleToBytes . DoubleVectorToBytes . EnsureBounds . MaxDouble . OnePointCrossOver . OnePointCrossOverOnDoublesUsingBytes . SizeOfDouble . SizeOfInt . SizeOfLong . TwoPointCrossOver . TwoPointCrossOverOnDoublesUsingBytes . UniformCrossOver . UniformCrossOverOnDoublesUsingBytes . arithmetic_crossover . blx_crossover . byte_crossover . byte_crossover_1p . byte_crossover_2p . byte_mutation . byte_mutation_dynamic . byte_mutation_random . byte_mutation_random_dynamic . flat_crossover . linear_crossover . mcga-internal . mcga-package . mcga . mcga2 . multi_mcga . sbx_crossover . unfair_average_crossover .
Some associated R codes: RcppExports.R . oplibrary.R . Full mcga package functions and examples
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