R package rgenoud: R version of GENetic Optimization Using Derivatives. A genetic algorithm plus derivative optimizer. Genoud is a function that combines evolutionary search algorithms with derivative-based (Newton or quasi-Newton) methods to solve difficult optimization problems. Genoud may also be used for optimization problems for which derivatives do not exist. Genoud , via the cluster option, supports the use of multiple computers, CPUs or cores to perform parallel computations.
Keywords for this software
References in zbMATH (referenced in 8 articles )
Showing results 1 to 8 of 8.
- Weber, Anett; Steiner, Winfried J.; Lang, Stefan: A comparison of semiparametric and heterogeneous store sales models for optimal category pricing (2017)
- Azzimonti, Dario; Bect, Julien; Chevalier, Clément; Ginsbourger, David: Quantifying uncertainties on excursion sets under a Gaussian random field prior (2016)
- Christoph Bergmeir and Daniel Molina and José Benítez: Memetic Algorithms with Local Search Chains in R: The Rmalschains Package (2016)
- Kang, Chaeryon; Janes, Holly; Huang, Ying: Combining biomarkers to optimize patient treatment recommendations (2014)
- Irincheeva, Irina; Cantoni, Eva; Genton, Marc G.: Generalized linear latent variable models with flexible distribution of latent variables (2012)
- Subramanian, Sundarraman: Model-based likelihood ratio confidence intervals for survival functions (2012)
- Zhang, Baqun; Tsiatis, Anastasios A.; Laber, Eric B.; Davidian, Marie: A robust method for estimating optimal treatment regimes (2012)
- Subramanian, Sundarraman; Dikta, Gerhard: Inverse censoring weighted median regression (2009)