mcga3.0.7 package

Machine Coded Genetic Algorithms for Real-Valued Optimization Problems

Performs arithmetic crossover operation on a pair of two selected pare...

Performs blx (blend) crossover operation on a pair of two selected par...

Performs crossover operation on a pair of two selected parent candidat...

Performs one-point crossover operation on a pair of two selected paren...

Performs two-point crossover operation on a pair of two selected paren...

Performs mutation operation on a given double vector

Performs mutation operation on a given double vector using dynamic mut...

Performs mutation operation on a given double vector

Performs mutation operation on a given double vector with dynamic muta...

Mutation operator for byte representation of double values

Mutation operator for byte representation of double values

Mutation operator for byte representation of double values

Converting `sizeof(double)`

bytes to a double value

Converting p * `sizeof(double)`

bytes to a vector of p double values

Byte representation of a `double`

typed variable

Byte representation of a vector of `double`

typed variables

Altering vector of doubles to satisfy boundary constraints

Performs flat crossover operation on a pair of two selected parent can...

Performs linear crossover operation on a pair of two selected parent c...

Maximum value of a `double`

typed variable

Internal mcga objects

Machine Coded Genetic Algorithms for Real-valued Optimization Problems

Performs machine coded genetic algorithms on a function subject to be ...

Performs a machine-coded genetic algorithm search for a given optimiza...

Performs multi objective machine coded genetic algorithms.

One Point Crossover operation on the two vectors of bytes

One-point Crossover operation on the two vectors of doubles using thei...

Performs sbx (simulated binary) crossover operation on a pair of two s...

Byte-length of a `double`

typed variable

Byte-length of a `int`

typed variable

Byte-length of a `long`

typed variable

Two Point Crossover operation on the two vectors of bytes

Two-point Crossover operation on the two vectors of doubles using thei...

Performs unfair average crossover operation on a pair of two selected ...

Uniform Crossover operation on the two vectors of bytes

Uniform Crossover operation on the two vectors of doubles using their ...

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.

Maintainer: Mehmet Hakan Satman License: GPL (>= 2) Last published: 2023-11-27