Expand description
Evolution strategy algorithms for global optimization
This module provides population-based optimization algorithms inspired by natural evolution, particularly the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) family.
§Algorithms
- CMA-ES: Covariance Matrix Adaptation Evolution Strategy with IPOP restart
- Step-size adaptation (cumulative step-size adaptation / CSA)
- Covariance matrix update (rank-1 and rank-mu updates)
- Population size adaptation
- IPOP-CMA-ES restart strategy (increasing population size)
- Boundary handling (reflection, projection, penalty)
Re-exports§
pub use cma_es::cma_es_minimize;pub use cma_es::BoundaryHandling;pub use cma_es::CmaEsOptions;pub use cma_es::CmaEsResult;pub use cma_es::CmaEsState;pub use cma_es::IpopCmaEs;pub use cma_es::RestartStrategy;
Modules§
- cma_es
- Covariance Matrix Adaptation Evolution Strategy (CMA-ES)