CRAN/E | mcga

mcga

Machine Coded Genetic Algorithms for Real-Valued Optimization Problems

Installation

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.

Citation mcga citation info

Key Metrics

Version 3.0.7
Published 2023-11-27 158 days ago
Needs compilation? yes
License GPL-2
License GPL-3
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Maintainer

Maintainer

Mehmet Hakan Satman

mhsatman@istanbul.edu.tr

Authors

Mehmet Hakan Satman

Material

Reference manual
Package source

In Views

Optimization

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

mcga archive

Depends

GA

Imports

Rcpp ≥ 0.11.4

LinkingTo

Rcpp