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

Felipe Campelo; Lucas Batista; Claus Aranha

doi:10.18637/jss.v092.i06

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

Felipe Campelo
, Lucas Batista
, Claus Aranha

Research output: Contribution to journal › Article › peer-review

20 Citations (Scopus)

166 Downloads (Pure)

Abstract

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.

Original language	English
Pages (from-to)	1-39
Journal	Journal of Statistical Software
Volume	92
Issue number	6
DOIs	https://doi.org/10.18637/jss.v092.i06
Publication status	Published - 23 Feb 2020

Bibliographical note

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.

Keywords

Component-oriented design
MOEA/D
Multiobjective evolutionary algorithms
R

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10.18637/jss.v092.i06Licence: CC BY 3.0

The MOEADr Package- AAMAccepted author manuscript, 965 KBLicence: CC BY 3.0
The MOEADr Package
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.
Final published version, 852 KBLicence: CC BY 3.0

https://arxiv.org/abs/1807.06731

Cite this

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title = "The MOEADr Package – A Component-Based Framework for Multiobjective Evolutionary Algorithms Based on Decomposition",

abstract = "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.",

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

Abstract

Bibliographical note

Keywords

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MOEADr: Component-Wise MOEA/D Implementation

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