CRAN/E | graDiEnt

graDiEnt

Stochastic Quasi-Gradient Differential Evolution Optimization

Installation

About

An optim-style implementation of the Stochastic Quasi-Gradient Differential Evolution (SQG-DE) optimization algorithm first published by Sala, Baldanzini, and Pierini (2018; doi:10.1007/978-3-319-72926-8_27). This optimization algorithm fuses the robustness of the population-based global optimization algorithm "Differential Evolution" with the efficiency of gradient-based optimization. The derivative-free algorithm uses population members to build stochastic gradient estimates, without any additional objective function evaluations. Sala, Baldanzini, and Pierini argue this algorithm is useful for 'difficult optimization problems under a tight function evaluation budget.' This package can run SQG-DE in parallel and sequentially.

github.com/bmgaldo/graDiEnt
Bug report File report

Key Metrics

Version 1.0.1
R ≥ 3.5.0
Published 2022-05-10 854 days ago
Needs compilation? no
License MIT
License File
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Maintainer

Maintainer

Brendan Matthew Galdo

Authors

Brendan Matthew Galdo

aut / cre

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Depends

R ≥ 3.5.0

Imports

stats
doParallel