Optimizers

Usage

Implement your own optimizer

Implemented optimizers

The following implementations of optimizers can found under the f3dasm.optimization module:

Pygmo implementations

These derivative-free global optimizers are ported from the pygmo Python library:

Name	Docs of the Python class	Reference
CMAES	f3dasm.optimization.pygmo_implementations.CMAES	pygmo cmaes
PSO	f3dasm.optimization.pygmo_implementations.PSO	pygmo pso_gen
SGA	f3dasm.optimization.pygmo_implementations.SGA	pygmo sga
XNES	f3dasm.optimization.pygmo_implementations.XNES	pygmo xnes

Scipy Implementations

These optimizers are ported from the scipy Python library:

Name	Docs of the Python class	Reference
CG	f3dasm.optimization.scipy_implementations.CG	scipy.minimize CG
DifferentialEvolution	f3dasm.optimization.scipy_implementations.DifferentialEvolution	scipy.optimize Differential Evolution
DualAnnealing	f3dasm.optimization.scipy_implementations.DualAnnealing	scipy.optimize Dual Annealing
LBFGSB	f3dasm.optimization.scipy_implementations.LBFGSB	scipy.minimize L-BFGS-B
NelderMead	f3dasm.optimization.scipy_implementations.NelderMead	scipy.minimize NelderMead

GPyOpt Implementations

Name	Docs of the Python class	Reference
Bayesian Optimization	f3dasm.optimization.gpyopt_implementations.BayesianOptimization	GPyOpt

Self implemented optimizers

Name	Docs of the Python class	Reference
Adam	f3dasm.optimization.gradient_based_algorithms.Adam	self implemented
Momentum	f3dasm.optimization.gradient_based_algorithms.Momentum	self implemented
SGD	f3dasm.optimization.gradient_based_algorithms.SGD	self implemented
RandomSearch	f3dasm.optimization.randomsearch.RandomSearch	self implemented