Module global

Module global 

Source
Expand description

Global optimization algorithms

This module provides various global optimization algorithms for finding the global minimum of a multivariate function.

Structs§

BasinHoppingOptions
Options for Basin-hopping algorithm
BayesianOptimizationOptions
Options for Bayesian optimization
BayesianOptimizer
The Bayesian optimization algorithm
ClusterCentroid
Cluster centroid information
ClusteringOptions
Configuration for clustering local minima
ClusteringResult
Result of clustering analysis
DifferentialEvolutionOptions
Options for Differential Evolution algorithm
DualAnnealingOptions
Options for Dual Annealing algorithm
LocalMinimum
Represents a local minimum found during optimization
MultiStartOptions
Options for multi-start optimization
ParticleSwarmOptions
Options for Particle Swarm Optimization
SimulatedAnnealingOptions
Options for Simulated Annealing
Space
Search space for parameters

Enums§

AcquisitionFunctionType
Acquisition function type enum for option selection
ClusteringAlgorithm
Clustering algorithms available
InitialPointGenerator
Initial point generator type
KernelType
Kernel type enum for option selection
Parameter
Parameter types for search space
StartPointStrategy
Strategy for generating starting points
StartingPointStrategy
Strategy for generating starting points

Functions§

basinhopping
Perform global optimization using basin-hopping
bayesian_optimization
Perform Bayesian optimization on a function
differential_evolution
Perform global optimization using differential evolution
dual_annealing
Perform global optimization using dual annealing
generate_diverse_start_points
Generate diverse starting points for multi-start optimization
multi_start
Perform multi-start optimization
multi_start_with_clustering
Multi-start optimization with clustering
particle_swarm
Perform global optimization using particle swarm optimization
simulated_annealing
Perform global optimization using simulated annealing