Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Felipe Campelo, Lucas S. Batista, Claus Aranha
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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Paper: The MOEADr Package: A Component-Based Framework for Multiobjective Evolutionary Algorithms Based on Decomposition     Download PDF (Downloads: 197)
Supplements:
MOEADr_1.1.1.tar.gz: R source package Download (Downloads: 16; 1MB)
v92i06-replication.zip: Replication materials Download (Downloads: 19; 381KB)

DOI: 10.18637/jss.v092.i06

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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.