Crate rlevo_evolution 

Tensor-native classical evolutionary algorithms for rlevo.

This crate ships the classical EA families — Genetic Algorithm (GA), Evolution Strategy (ES), Evolutionary Programming (EP), Differential Evolution (DE), and Cartesian Genetic Programming (CGP) — on top of the Burn tensor abstraction, with GPU acceleration via custom CubeCL kernels on hot paths.

Surface area

• strategy — the central Strategy trait and the EvolutionaryHarness adapter that wraps any strategy into rlevo-benchmarks::BenchEnv.
• genome — zero-sized marker types (Real, Binary, Integer, Tree) that parameterize the operator set.
• population — Population<B, K>, a thin wrapper around Tensor<B, 2> carrying shape metadata.
• fitness — FitnessFn / BatchFitnessFn and the FromFitnessEvaluable adapter for rlevo-benchmarks::FitnessEvaluable.
• rng — deterministic seed streams (splitmix64) for reproducibility.
• shaping — fitness shaping transforms (centered rank, z-score).
• ops — selection, crossover, mutation, and replacement operators.
• algorithms — concrete strategies.

Re-exports

pub use strategy::EvolutionaryHarness;

pub use strategy::Strategy;

pub use strategy::StrategyMetrics;

Modules

algorithms

Concrete evolutionary algorithms.

fitness

Fitness evaluation traits and adapters.

genome

Genome category trait and its zero-sized marker types.

ops

Evolutionary operators.

population

Population containers.

rng

Deterministic seed derivation for strategies.

shaping

Fitness shaping transforms.

strategy

Central Strategy trait and the EvolutionaryHarness adapter.