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 (may not be active yet)
Author: Rogelio Salinas Gutiérrez ORCID iD [aut, cre, cph], Cristina Díaz Esquivel ORCID iD [aut, cph], Angela María Gallegos Martínez ORCID iD [aut, cph], Agustín Moreno Cruz ORCID iD [aut, cph], Miguel Angel Moreno Urbina ORCID iD [aut, cph], Pedro Abraham Montoya Calzada ORCID iD [aut, cph], Carlos Alberto López Hernández ORCID iD [aut, cph], Ilse Daniela Saldivar Olvera ORCID iD [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: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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