jMetal: A Java framework for multi-objective optimization

By Juan José Durillo, Antonio J. Nebro. Advances in Engineering Software, 2011

1,165 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/72f6c921afd9056c03dc6db0151b539e3ae699a3

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Citations in the corpus

Consistencies and Contradictions of Performance Metrics in Multiobjective Optimization (2014, methodology): “provide a quantitative comparison of different optimal solution sets in multiobjective optimization (MOO) [1]–[5].”
A Framework for Large-Scale Multiobjective Optimization Based on Problem Transformation (2018, methodology): “With the exception of the CCGDE3 algo-rithm, we rely on the jMetal framework for Java, version 4.5 [30] for the implementation of the algorithms.”
Recent advances in selection hyper-heuristics (2020, background): “…of multiobjective hyper-heuristic studies in the literature which use existing software libraries for multiobjective optimisation, such as, PISA accessible at http://www.tik.ee.ethz.ch/pisa/ (Bleuler et al., 2003) and jMetal accessible at http://jmetal.sourceforge.net/ (Durillo and Nebro, 2011).”
A Decomposition-Based Evolutionary Algorithm for Many Objective Optimization (2015, methodology): “IGD value is computed using the targeted reference set of 2429 solutions reported in [47] and”
Pymoo: Multi-Objective Optimization in Python (2020, methodology): “Recently, the well-known multi-objective optimization framework jMetal [15] developed in Java [19] has been ported to a Python version, namely jMetalPy [2].”
A Tutorial On the design, experimentation and application of metaheuristic algorithms to real-World optimization problems (2021, background): “3 July 2019 jMetal [115][116] Java SO/MO MIT 5.”
COCO: a platform for comparing continuous optimizers in a black-box setting (2016, background): “Newer platforms that attempt to benchmark multiobjective solvers are the MOEA Framework (in Java), its Python counterpart Platypus, jMetal (originally in Java, now also in other languages) [25], PLATEMO (in Matlab) [67], and ecr (in R) [14].”
A New Dominance Relation-Based Evolutionary Algorithm for Many-Objective Optimization (2016, methodology): “All the concerned algorithms including the proposed θ-DEA are implemented in the jMetal framework [77], and run on an Intel 2.”
Balancing Convergence and Diversity in Decomposition-Based Many-Objective Optimizers (2016, methodology): “All MOEAs including MOEA/D-DU and EFR-RR are implemented in the jMetal framework [62], and run on an Intel Core i7 2.”
Distributed evolutionary algorithms and their models: A survey of the state-of-the-art (2015, methodology): “To make further improvement, parallel nd distributed versions of MOEA/D are developed in [92,36,32,33].”
An easy-to-use real-world multi-objective optimization problem suite (2020, methodology): “We used the jMetal 4.5 framework [57] for algorithm implementation.”
A Method for a Posteriori Identification of Knee Points Based on Solution Density (2018, methodology): “The basic evolutionary optimization framework is based on SPEA-II [2], and all compared algorithms are implemented in jMtal [31].”