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metaheuristicOpt  

Metaheuristic for Optimization
View on CRAN: Click here


Download and install metaheuristicOpt package within the R console
Install from CRAN:
install.packages("metaheuristicOpt")

Install from Github:
library("remotes")
install_github("cran/metaheuristicOpt")

Install by package version:
library("remotes")
install_version("metaheuristicOpt", "2.0.0")



Attach the package and use:
library("metaheuristicOpt")
Maintained by
Lala Septem Riza
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-10-16
Latest Update: 2019-06-19
Description:
An implementation of metaheuristic algorithms for continuous optimization. Currently, the package contains the implementations of 21 algorithms, as follows: particle swarm optimization (Kennedy and Eberhart, 1995), ant lion optimizer (Mirjalili, 2015 ), grey wolf optimizer (Mirjalili et al., 2014 ), dragonfly algorithm (Mirjalili, 2015 ), firefly algorithm (Yang, 2009 ), genetic algorithm (Holland, 1992, ISBN:978-0262581110), grasshopper optimisation algorithm (Saremi et al., 2017 ), harmony search algorithm (Mahdavi et al., 2007 ), moth flame optimizer (Mirjalili, 2015 , sine cosine algorithm (Mirjalili, 2016 ), whale optimization algorithm (Mirjalili and Lewis, 2016 ), clonal selection algorithm (Castro, 2002 ), differential evolution (Das & Suganthan, 2011), shuffled frog leaping (Eusuff, Landsey & Pasha, 2006), cat swarm optimization (Chu et al., 2006), artificial bee colony algorithm (Karaboga & Akay, 2009), krill-herd algorithm (Gandomi & Alavi, 2012), cuckoo search (Yang & Deb, 2009), bat algorithm (Yang, 2012), gravitational based search (Rashedi et al., 2009) and black hole optimization (Hatamlou, 2013).
How to cite:
Lala Septem Riza (2017). metaheuristicOpt: Metaheuristic for Optimization. R package version 2.0.0, https://cran.r-project.org/web/packages/metaheuristicOpt. Accessed 09 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:29), 1.0.0 (2017-10-16 14:15)
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Complete documentation for metaheuristicOpt
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