Article thumbnail

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

By Felipe Campelo, Lucas S. Batista and Claus Aranha

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

Topics: MOEA/D; multiobjective evolutionary algorithms; R; component-oriented design, QA76.75-76.765 Computer Software
Publisher: 'Foundation for Open Access Statistic'
Year: 2020
DOI identifier: 10.18637/jss.v092.i06
OAI identifier: oai:ojs.jstatsoft.uibk.ac.at:article/3267
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • https://www.jstatsoft.org/inde... (external link)

  • To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.

    Suggested articles