Have a look at NLOPT optimiser package - Githubissues

pints-team / pints

Probabilistic Inference on Noisy Time Series

http://pints.readthedocs.io

Other

229 stars 33 forks source link

Have a look at NLOPT optimiser package #54

Closed MichaelClerx closed 5 years ago

MichaelClerx commented 7 years ago

https://nlopt.readthedocs.io/en/latest/NLopt_Algorithms/

MichaelClerx commented 7 years ago

Global derivative-free optimisers:

Direct/Direct-L:
- NLOPT_GN_DIRECT_L
- NLOPT_GN_DIRECT
- NLOPT_GN_DIRECT_L_RAND
- NLOPT_GNL_DIRECT_NOSCAL
- NLOPT_GN_DIRECT_L_NOSCAL
- NLOPT_GN_DIRECT_L_RAND_NOSCAL
CRS
- NLOPT_GN_CRS2_LM
ISRES
- NLOPT_GN_ISRES
ESCH
- NLOPT_GN_ESCH

Local derivative-free optimisers:

COBYLA (Also in SciPy, doesn't really work)
- NLOPT_LN_COBYLA
BOBYQA
- NLOPT_LN_BOBYQA
- NLOPT_LN_NEWUOA_BOUND
Principal axis
- NLOPT_LN_PRAXIS
Simplex / Nelder-Mead (also in SciPy)
- NLOPT_LN_NELDERMEAD
Subplex
- NLOPT_LN_SBPLX

So seems worth a try