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.
|Imports:||Rcpp (≥ 0.11.4)|
|Author:||Mehmet Hakan Satman|
|Maintainer:||Mehmet Hakan Satman <mhsatman at istanbul.edu.tr>|
|License:||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]|
|Citation:||mcga citation info|
|CRAN checks:||mcga results|
|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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