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Project Summary

The minfx project is a Python package for numerical optimisation, being a large collection of standard minimisation algorithms. This includes the line search methods: steepest descent, back-and-forth coordinate descent, quasi-Newton BFGS, Newton, Newton-CG; the trust-region methods: Cauchy point, dogleg, CG-Steihaug, exact trust region; the conjugate gradient methods: Fletcher-Reeves, Polak-Ribiere, Polak-Ribiere +, Hestenes-Stiefel; the miscellaneous methods: Grid search, Simplex, Levenberg-Marquardt; and the augmented function constraint algorithms: logarithmic barrier and method of multipliers (or augmented Lagrangian method).

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algorithm conjugate_gradient library line_search local_optimisation minimisation minimization nonlinear numerical optimisation optimization python trust_region

In a Nutshell, minfx...

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These details are provided for information only. No information here is legal advice and should not be used as such.

This Project has No vulnerabilities Reported Against it

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30 Day Summary

Apr 5 2021 — May 5 2021

12 Month Summary

May 5 2020 — May 5 2021

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