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.
Version: | 3.0.1 |
Depends: | GA |
Imports: | Rcpp (≥ 0.11.4) |
LinkingTo: | Rcpp |
Published: | 2016-05-12 |
Author: | Mehmet Hakan Satman |
Maintainer: | Mehmet Hakan Satman <mhsatman at istanbul.edu.tr> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
Citation: | mcga citation info |
In views: | Optimization |
CRAN checks: | mcga results |
Reference manual: | mcga.pdf |
Package source: | mcga_3.0.1.tar.gz |
Windows binaries: | r-devel: mcga_3.0.1.zip, r-release: mcga_3.0.1.zip, r-oldrel: mcga_3.0.1.zip |
OS X El Capitan binaries: | r-release: mcga_3.0.1.tgz |
OS X Mavericks binaries: | r-oldrel: mcga_3.0.1.tgz |
Old sources: | mcga archive |
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