Metaheuristics aim to generate or select a heuristic for an optimization problem, particularly where the set of sample solutions is too large to completely sample.
A handful of metaheuristic crates exists in the Rust ecosystem, most notably several libraries that make it straight-forward to write genetic or evolutionary algorithms.
Mathematical optimization in pure Rust
Find approximate solutions to your optimisation problem using metaheuristics algorithms
Fast, parallel, extensible and adaptable genetic algorithm library.
Flexible and modular single or multi-objective solver for contiguous and discrete problems
A Rust implementation of the Simple(x) black-box optimization algorithm.
Evolutionary algorithms library written in Rust.
A library providing genetic algorithm execution.
Rust implementation of real-coded genetic algorithm for solving optimization problems and training of neural networks. The latter is also known as neuroevolution.
Evolutionary Algorithm Library for Rust
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