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

arXiv: https://arxiv.org/abs/1807.06731 · HTML: https://mlsanity.com/paper/1807.06731/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jul 2018.

## Built on by (most cited first, 4 of 4)

- [Search Trajectories Networks of Multiobjective Evolutionary Algorithms](https://mlsanity.com/paper/2201.11726/) (2022)
- [Faster Convergence in Multi-Objective Optimization Algorithms Based on Decomposition](https://mlsanity.com/paper/2112.11939/) (2021)
- [Component-wise Analysis of Automatically Designed Multiobjective Algorithms on Constrained Problems](https://mlsanity.com/paper/2203.13447/) (2022)
- [Multiobjective Evolutionary Component Effect on Algorithm behavior](https://mlsanity.com/paper/2308.02527/) (2023)

## Abstract (arXiv)

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.