math-differential-evolution

Crates.iomath-differential-evolution
lib.rsmath-differential-evolution
version0.3.2
created_at2025-12-21 12:57:17.753848+00
updated_at2026-01-09 21:40:51.608526+00
descriptionNon linear optimisation library with own DE solvers and interface to NLOpt and MetaHeuristics
homepage
repositoryhttps://github.com/pierreaubert/math-audio
max_upload_size
id1997924
size375,533
Pierre Aubert (pierreaubert)

documentation

README

Math Audio Differential Evolution

This crate provides a pure Rust implementation of Differential Evolution (DE) global optimization algorithm with advanced features.

Features

  • Pure Rust Implementation: No external dependencies for core optimization
  • Multiple DE Strategies: Various mutation and crossover strategies
  • Constraint Handling: Linear and nonlinear constraint support
  • Adaptive Parameters: Self-adjusting F and CR parameters
  • Evaluation Recording: Track optimization progress and convergence
  • Visualization Tools: Plot test functions and optimization traces

Optimization Strategies

Mutation Strategies

  • DE/rand/1: x_trial = x_r1 + F * (x_r2 - x_r3)
  • DE/best/1: x_trial = x_best + F * (x_r1 - x_r2)
  • DE/current-to-best/1: Combines current and best vectors
  • DE/rand/2: Uses five random vectors for mutation

Crossover Strategies

  • Binomial: Random parameter-wise crossover
  • Exponential: Sequential parameter crossover

Usage

use math_audio_differential_evolution::{differential_evolution, DEConfig, Strategy, Mutation};
use ndarray::Array1;

// Example objective function (Rosenbrock)
let objective = |x: &Array1<f64>| {
    let a = 1.0;
    let b = 100.0;
    (a - x[0]).powi(2) + b * (x[1] - x[0].powi(2)).powi(2)
};

// Define bounds for 2D problem
let bounds = vec![(-5.0, 5.0), (-5.0, 5.0)];

let config = DEConfig {
    strategy: Strategy::Rand1Bin,
    maxiter: 1000,
    popsize: 50,
    mutation: Mutation::Factor(0.8),
    recombination: 0.9,
    seed: Some(42),
    ..Default::default()
};

let result = differential_evolution(&objective, &bounds, config)
    .expect("optimization should succeed");
println!("Best solution: {:?}", result.x);
println!("Best fitness: {}", result.fun);

Constraint Support

Linear Constraints

use math_audio_differential_evolution::{LinearConstraintHelper, DEConfig};
use ndarray::{Array1, Array2};

// Linear constraint: x1 + x2 <= 1.0
let constraint = LinearConstraintHelper {
    a: Array2::from_shape_vec((1, 2), vec![1.0, 1.0]).unwrap(),
    lb: Array1::from_vec(vec![f64::NEG_INFINITY]),
    ub: Array1::from_vec(vec![1.0]),
};

// Apply to configuration with penalty weight
let mut config = DEConfig::default();
constraint.apply_to(&mut config, 1000.0); // penalty weight

Nonlinear Constraints

let nonlinear_constraint = |x: &[f64]| -> f64 {
    x[0].powi(2) + x[1].powi(2) - 1.0 // circle constraint
};

Visualization

The crate includes a plot_functions binary for visualizing test functions and optimization traces:

# Plot test functions as contour plots
cargo run --bin plot_functions -- --functions rosenbrock,sphere

# Show optimization traces from CSV files
cargo run --bin plot_functions -- --csv-dir traces/ --show-traces

Integration

This crate is part of the Math Audio ecosystem:

  • Used by autoeq for filter parameter optimization
  • Integrates with math-audio-testfunctions for validation
  • Works with math-audio-iir-fir for audio filter optimization

Examples

The crate includes several example programs demonstrating different DE capabilities:

  • basic_de: Simple unconstrained optimization
  • linear_constraints: Linear constraint handling
  • nonlinear_constraints: Complex constraint optimization

References

License

GPL-3.0-or-later

Commit count: 39

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