TY - JOUR
T1 - The MOEADr Package – A Component-Based Framework for Multiobjective Evolutionary Algorithms Based on Decomposition
AU - Campelo, Felipe
AU - Batista, Lucas
AU - Aranha, Claus
N1 - This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.
PY - 2020/2/23
Y1 - 2020/2/23
N2 - 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.
AB - 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.
KW - Component-oriented design
KW - MOEA/D
KW - Multiobjective evolutionary algorithms
KW - R
UR - https://www.jstatsoft.org/article/view/v092i06
UR - http://www.scopus.com/inward/record.url?scp=85081605956&partnerID=8YFLogxK
U2 - 10.18637/jss.v092.i06
DO - 10.18637/jss.v092.i06
M3 - Article
SN - 1548-7660
VL - 92
SP - 1
EP - 39
JO - Journal of Statistical Software
JF - Journal of Statistical Software
IS - 6
ER -