jMetal project Web site

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jMetal is a Java-based framework for multi-objective optimization with metaheuristics. The last stable version is 7.9. The most recent documentation is hosted in https://jmetal.readthedocs.io.

jMetal 7.9 is a Maven project structured in the following sub-projects:

+---------------------+------------------------------------+ | Sub-project | Contents | +=====================+====================================+ | jmetal-core | Core classes | +---------------------+------------------------------------+ | jmetal-algorithm | Algorithm implementations | +---------------------+------------------------------------+ | jmetal-problem | Benchmark problems | +---------------------+------------------------------------+ | jmetal-lab | Experimentation and visualization | +---------------------+------------------------------------+ | jmetal-parallel | Parallel extensions | +---------------------+------------------------------------+ | jmetal-auto | Auto-design and configuration | +---------------------+------------------------------------+ | jmetal-component | Component-based algorithms | +---------------------+------------------------------------+

.. note::

jMetal 7.6 is the last version in which jmetal-auto is updated. From now on this sub-project is frozen, as its functionality is covered by the Evolver <https://github.com/jMetal/Evolver>_ project, which is under active development.

Related projects

• jMetalPy <https://github.com/jMetal/jmetalpy>_: jMetal in Python
• SAES <https://github.com/jMetal/SAES>_: Python library to analyse and compare the performance of multi-objective algorithms
• Evolver <https://github.com/jMetal/Evolver>_: Java framework for the automated meta-optimization of multi-objective metaheuristics, which formulates their automatic configuration and design as a multi-objective optimization problem
• Evolver-Studio <https://github.com/jMetal/Evolver-Studio>_: graphical interface for Evolver (Python/Streamlit application)

Python scripts (NEW)

The scripts/ directory contains Python utilities for visualising Pareto fronts produced by jMetal algorithms (any FUN.csv file):

+-------------------------------+--------------------------------------------------------+ | Script | Description | +===============================+========================================================+ | plot_front.py | Static matplotlib figure (2D/3D scatter, parallel | | | coordinates for >3 objectives). Saves to PNG/PDF/SVG. | +-------------------------------+--------------------------------------------------------+ | plot_front_interactive.py | Interactive Plotly viewer (rotate 3D fronts, hover for | | | values). Opens in the browser or saves as HTML. | +-------------------------------+--------------------------------------------------------+

Install dependencies and run::

# venv
python -m venv .venv && source .venv/bin/activate
pip install -r scripts/requirements.txt

# conda
conda create -n jmetal python=3.11 && conda activate jmetal
pip install -r scripts/requirements.txt

# Usage examples
python scripts/plot_front.py FUN.csv
python scripts/plot_front.py FUN.csv referenceFront.csv --mode side --output fig.png
python scripts/plot_front_interactive.py FUN.csv referenceFront.csv --mode both

Changelog

• [10/29/2026] Fixes that change results: the CURRENT_TO_RAND_1_BIN and CURRENT_TO_RAND_1_EXP variants of DifferentialEvolutionCrossover had no mutation (every mutated variable was set to 0), and CF10 did not count its second constraint in the violation. Results obtained with them in earlier versions are not valid.

• [10/26/2026] The LIR-CMOP problems follow the paper (Fan et al., 2019): their definitions change, so the results obtained with LIRCMOP5 to LIRCMOP14 in earlier versions are not comparable, and they have exact reference fronts.

• [10/26/2026] The constrained problems DC1-DTLZ1 to DC3-DTLZ3 (package dcdtlz) and CF1 to CF10 of the CEC 2009 competition (package cec2009, classes CEC2009CF1 to CEC2009CF10), with their reference fronts.

• [10/23/2026] jMetal 7.9 is released. Changes that can affect existing code or results: the problems of the CEC 2021 suite are named RCM01 to RCM50; the random selection of the algorithms and the normalization of SMS-EMOA and NSGA-III have changed, so the results for a given seed are not the same as in 7.8; the quality indicators and NormalizeUtils reject invalid fronts with an exception. See the changelog section of the documentation for the complete list.

• [10/23/2026] Constraint-handling techniques (package org.uma.jmetal.util.constrainthandling): the constrained-domination principle, the epsilon-constrained method, push and pull search, stochastic ranking and the self-adaptive penalty, which the component-based NSGA-II, NSGA-III, SMS-EMOA, AGE-MOEA, RDSMOEA, PAES, SMPSO and MOEA/D take with setConstraintHandlingTechnique. Termination gives the progress of the run, which the techniques that change during the run use. See the constraints section <https://jmetal.readthedocs.io/en/latest/constraints.html>_.

• [10/23/2026] Random numbers in parallel threads: ThreadLocalRandomGenerator gives each thread its own generator, ExecuteAlgorithms installs it with more than one core and runs on as many threads as cores, and ExperimentBuilder.setSeed makes a parallel experiment reproducible. The random selection draws only the selected elements, so the results for a given seed change.

• [10/23/2026] Reference fronts of the CRE problems and of the CEC 2021 suite, whose problems are now named RCM01 to RCM50, and a page on the constrained benchmarks and their reference fronts in the documentation.

• [10/22/2026] Fixes in the normalization of the fronts (, , the classic and the component-based NSGA-III), the hypervolume with negative reference points, the hypervolume contributions of SMS-EMOA with four or more objectives, and the argument checks of the quality indicators.

The complete list of changes is available in the changelog section of the documentation <https://jmetal.readthedocs.io/en/latest/changelog.html>_.