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MetaheuRUSTics

A comprehensive collection of metaheuristic optimization algorithms implemented in Rust. This library provides efficient implementations of popular optimization algorithms along with visualization tools.

Features

  • Multiple optimization algorithms:

    • Particle Swarm Optimization (PSO)
    • Differential Evolution (DE)
    • Genetic Algorithm (GA)
    • Simulated Annealing (SA)
    • Adaptive Chaotic Grey Wolf Optimizer (ACGWO)
    • Artificial Bee Colony Optimization (ABCO)
    • Grey Wolf Optimizer (GWO)
    • Firefly Algorithm (FA)

  • Test functions for benchmarking:

    • Sphere Function
    • Ackley Function
    • Rosenbrock Function
    • Rastrigin Function
    • Beale Function
    • Griewank Function

  • Visualization tools:

    • Surface plots
    • Contour plots
    • Convergence plots

Installation

Add this to your Cargo.toml:

[dependencies]
metaheurustics = "0.2.0"

Quick Start

Here's a simple example using PSO to optimize the Sphere function:

use metaheurustics::prelude::*;
use metaheurustics::algorithm::pso::{PSO, PSOParams};
use metaheurustics::test_function::Sphere;

fn main() {
    let sphere = Sphere::new();
    let pso_params = PSOParams::default();
    let pso = PSO::new(&sphere, pso_params);
    
    let result = pso.optimize();
    println!("Best solution: {:?}", result.best_solution);
    println!("Best fitness: {}", result.best_fitness);
}

Examples

Check out the examples directory for more detailed usage:

  • examples/plot_all.rs: Demonstrates visualization of all algorithms on different test functions
  • examples/simple_optimization.rs: Shows basic usage of each optimization algorithm

Documentation

For detailed documentation, visit docs.rs/metaheurustics

Benchmarks

The library includes comprehensive benchmarks comparing the performance of different algorithms on various test functions. Run the benchmarks using:

cargo bench

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.