Stochastic Quasi-Gradient Differential Evolution Optimization R package graDiEnt version 1.0.1 CRAN Task View: Optimization (https://CRAN.R-project.org/view=Optimization) 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. Software Depends: R (>= 3.5.0) Imports: stats, doParallel Brendan Matthew Galdo <Brendan.m.galdo@gmail.com> Comprehensive R Archive Network (CRAN) Brendan Matthew Galdo [aut, cre] (ORCID: <https://orcid.org/0000-0002-1279-3859>) MIT + file LICENSE (https://CRAN.R-project.org/package=graDiEnt/LICENSE) 2022-05-10 application/tgz https://CRAN.R-project.org/package=graDiEnt doi:10.32614/CRAN.package.graDiEnt