A high-performance Rust library for numerical optimization, providing efficient implementations of algorithms for linear and nonlinear programming.

Copters is designed to be a comprehensive optimization toolkit for Rust, offering a wide range of algorithms for solving constrained and unconstrained optimization problems. Built on top of the faer linear algebra library, it provides both ease of use and performance.

• Revised Simplex Method - Memory-efficient variant of the simplex method
• Revised Dual Simplex - For problems starting with dual feasibility
• Mehrotra Predictor-Corrector - Polynomial-time algorithms for large-scale linear programs

• ADMM (Alternating Direction Method of Multipliers) - For distributed and constrained convex optimization
• Conjugate Gradient - For quadratic and nonlinear optimization

• Proximal Gradient Descent - First-order optimization method
• Accelerated Gradient Descent - Nesterov and momentum-based methods
• Stochastic Gradient Descent - For problems with uncertainty (stochastic programs)
• Interior Point Method - For nonlinear programs with constraints

1. Performance: Leverage Rust's zero-cost abstractions and the efficient faer linear algebra library
2. Correctness: Extensive testing and validation against known optimization problems
3. Flexibility: Pluggable objective functions, constraints, and stopping criteria
4. Usability: Intuitive API with sensible defaults
5. Modularity: Use only the algorithms you need

This library is in early development. APIs are subject to change.

Current status:

• Project structure and dependencies
• Basic linear algebra utilities
• Core algorithm implementations (in progress)
• Documentation and examples
• Comprehensive test suite
• Benchmarks

• Support for automatic differentiation
• Python bindings via PyO3

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

# Build the library
cargo build

# Run tests
cargo test

# Generate documentation
cargo doc --open

• Optimization.jl - Julia optimization framework
• scipy.optimize - Python optimization toolkit
• COIN-OR - C++ optimization libraries
• HiGHS - Revised simplex method

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

If you use Copters in your research, please cite:

@software{copters,
  author = {Avinash Madavan},
  title = {Copters: A Rust Library for Numerical Optimization},
  year = {2026},
  url = {https://github.com/amadavan/copters}
}

Avinash Madavan - avinash.madavan@gmail.com

Project Link: https://github.com/amadavan/copters

AI Disclosure: This project makes limited use of AI-assisted tooling. AI is employed for debugging assistance, boilerplate generation, and drafting documentation. All algorithm design, core implementation, and architectural decisions, unless explicitly specified, are made by the author. AI-generated content is reviewed before inclusion.