MetaEEEA: Metaheuristic Algorithms with Explicit Exploration

Solves single-objective optimization problems by using bio-inspired metaheuristic algorithms. The implemented metaheuristics are the Butterfly Optimization Algorithm, the Ladybug Beetle Optimization Algorithm and the Prairie Dog Optimization Algorithm. For all these optimization algorithms, the search of optimal values can be reinforced with the explicit exploration strategy proposed by Salinas-Gutiérrez and Muñoz Zavala (2023) <doi:10.1016/j.asoc.2023.110230>.

Version:	1.0.0
Imports:	EEEA
Suggests:	testthat (≥ 3.0.0)
Published:	2026-07-24
DOI:	10.32614/CRAN.package.MetaEEEA
Author:	Rogelio Salinas Gutiérrez [aut, cre, cph], Cristina Díaz Esquivel [aut, cph], Angela María Gallegos Martínez [aut, cph], Agustín Moreno Cruz [aut, cph], Miguel Angel Moreno Urbina [aut, cph], Pedro Abraham Montoya Calzada [aut, cph], Carlos Alberto López Hernández [aut, cph], Ilse Daniela Saldivar Olvera [aut, cph]
Maintainer:	Rogelio Salinas Gutiérrez <rogelio.salinas at edu.uaa.mx>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	MetaEEEA results

Documentation:

Reference manual:

MetaEEEA.html , MetaEEEA.pdf

Downloads:

Package source:	MetaEEEA_1.0.0.tar.gz
Windows binaries:	r-devel: MetaEEEA_1.0.0.zip, r-release: not available, r-oldrel: MetaEEEA_1.0.0.zip
macOS binaries:	r-release (arm64): MetaEEEA_1.0.0.tgz, r-oldrel (arm64): MetaEEEA_1.0.0.tgz, r-release (x86_64): MetaEEEA_1.0.0.tgz, r-oldrel (x86_64): MetaEEEA_1.0.0.tgz

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