The MOEADr Package: A Component-Based Framework for Multiobjective Evolutionary Algorithms Based on Decomposition

Multiobjective evolutionary algorithms based on decomposition (MOEA/D) represent a widely used class of population-based metaheuristics for the solution of multicriteria optimization problems. We introduce the MOEADr package, which offers many of these variants as instantiations of a component-orien...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Journal of statistical software Ročník 92; číslo 6; s. 1 - 39
Hlavní autori:	Campelo, Felipe, Batista, Lucas S., Aranha, Claus
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Foundation for Open Access Statistics 01.02.2020
Predmet:	component-oriented design moea/d multiobjective evolutionary algorithms
ISSN:	1548-7660, 1548-7660
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Popis
Shrnutí:	Multiobjective evolutionary algorithms based on decomposition (MOEA/D) represent a widely used class of population-based metaheuristics for the solution of multicriteria optimization problems. We introduce the MOEADr package, which offers many of these variants as instantiations of a component-oriented framework. This approach contributes for easier reproducibility of existing MOEA/D variants from the literature, as well as for faster development and testing of new composite algorithms. The package offers an standardized, modular implementation of MOEA/D based on this framework, which was designed aiming at providing researchers and practitioners with a standard way to discuss and express MOEA/D variants. In this paper we introduce the design principles behind the MOEADr package, as well as its current components. Three case studies are provided to illustrate the main aspects of the package.
ISSN:	1548-7660 1548-7660
DOI:	10.18637/jss.v092.i06