genevo

genevo provides building blocks to run simulations of optimization and search problems using genetic algorithms (GA).

The vision for genevo is to be a flexible and greatly extensible framework for implementing genetic algorithm applications.

genevo is written in Rust. The library's API utilizes lots of traits and types for modelling the domain of genetic algorithms.

Usage

Add this to your Cargo.toml:

[dependencies]
genevo = "0.1"

And add this to your crate:

extern crate genevo;

Have a look at the examples to see how to use this crate:

monkeys: explores the idea of Shakespeare's monkeys, also known as the infinite monkey theorem
queens: searches for solutions of the N Queens Problem

[JFGA]: Jeremy Fisher: Genetic Algorithms

[OBI98]: Marek Obitko: Genetic Algorithms Tutorial

[GEAT]: GEATbx: Evolutionary Algorithms

[IGAYT]: Noureddin Sadawi: A Practical Introduction to Genetic Algorithms

[CT9YT]: The Coding Train: 9: Genetic Algorithms - The Nature of Code

[BT95]: Tobias Blickle, Lothar Thiele, 1995: A Comparison of Selection Schemes used in Genetic Algorithms.

[RRCGH]: StefanoD: Rust_Random_Choice Rust library.

[TSP95]: TSPLIB95: library of sample instances for the TSP (and related problems)