genevo
A flexible Rust framework for building and running genetic algorithm simulations for optimization and search problems.
What is genevo?
Genevo is a Rust framework for implementing genetic algorithm simulations to solve optimization and search problems. It provides a modular, trait-based architecture that models the domain of genetic algorithms, allowing developers to customize every component while offering sensible defaults. The library enables experimentation with different selection, crossover, mutation, and termination strategies to find optimal solutions for problems like the knapsack problem or N-Queens.
Rust developers and researchers working on optimization, search problems, or evolutionary computation who need a flexible, extensible framework for genetic algorithm simulations. It's also suitable for educators and students learning about genetic algorithms through practical implementation.
Developers choose Genevo for its extreme flexibility—every component is a trait that can be customized—combined with comprehensive built-in implementations that work out of the box. Its Rust foundation ensures performance and safety, while WASM support enables browser-based simulations, making it unique among GA libraries.
Overview
Execute genetic algorithm (GA) simulations in a customizable and extensible way.
Use Cases
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