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PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization

arXiv 1701.00879 ↗First posted 4 Jan 2017cs.NEcited by 41

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Abstract (arXiv)

Over the last three decades, a large number of evolutionary algorithms have been developed for solving multiobjective optimization problems. However, there lacks an up-to-date and comprehensive software platform for researchers to properly benchmark existing algorithms and for practitioners to apply selected algorithms to solve their real-world problems. The demand of such a common tool becomes even more urgent, when the source code of many proposed algorithms has not been made publicly available. To address these issues, we have developed a MATLAB platform for evolutionary multi-objective optimization in this paper, called PlatEMO, which includes more than 50 multi-objective evolutionary algorithms and more than 100 multi-objective test problems, along with several widely used performance indicators. With a user-friendly graphical user interface, PlatEMO enables users to easily compare several evolutionary algorithms at one time and collect statistical results in Excel or LaTeX files. More importantly, PlatEMO is completely open source, such that users are able to develop new algorithms on the basis of it. This paper introduces the main features of PlatEMO and illustrates how to use it for performing comparative experiments, embedding new algorithms, creating new test problems, and developing performance indicators. Source code of PlatEMO is now available at: http://bimk.ahu.edu.cn/index.php?s=/Index/Software/index.html.

Key facts. Cited by 41 papers in the map (data through 14 Oct 2026). First posted on arXiv 4 Jan 2017.

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Citing papers per year: 2021: 9; 2022: 7; 2023: 8; 2024: 7; 2025: 8; 2026: 2.

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  1. 2022Multi-agent Dynamic Algorithm Configurationcited by 36
  2. 2023Large Language Model for Multi-objective Evolutionary Optimizationcited by 29
  3. 2021Meta-Learning-Based Deep Reinforcement Learning for Multiobjective Optimization Problemscited by 20
  4. 2022Neural Architecture Search as Multiobjective Optimization Benchmarks: Problem Formulation and Performance Assessmentcited by 17
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  6. 2025A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solvingcited by 11
  7. 2024LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorchcited by 10
  8. 2021A Federated Data-Driven Evolutionary Algorithm for Expensive Multi/Many-objective Optimizationcited by 5
  9. 2024A Tutorial on the Design, Experimentation and Application of Metaheuristic Algorithms to Real-World Optimization Problemscited by 5
  10. 2021Multi-objective Feature Selection with Missing Data in Classificationcited by 4
  11. 2024Model Uncertainty in Evolutionary Optimization and Bayesian Optimization: A Comparative Analysiscited by 4
  12. 2021Attention-Guided Black-box Adversarial Attacks with Large-Scale Multiobjective Evolutionary Optimizationcited by 3
29 more
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  2. 2022Assessing Ranking and Effectiveness of Evolutionary Algorithm Hyperparameters Using Global Sensitivity Analysis Methodologiescited by 3
  3. 2025MAS-KCL: Knowledge component graph structure learning with large language model-based agentic workflowcited by 3
  4. 2024Expected Coordinate Improvement for High-Dimensional Bayesian Optimizationcited by 2
  5. 2026Evolutionary Biparty Multiobjective UAV Path Planning: Problems and Empirical Comparisonscited by 2
  6. 2021PICA: A Pixel Correlation-based Attentional Black-box Adversarial Attackcited by 1
  7. 2022Benchmarking Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimizationcited by 1
  8. 2022GPSAF: A Generalized Probabilistic Surrogate-Assisted Framework for Constrained Single- and Multi-objective Optimizationcited by 1
  9. 2022Molecule optimization via multi-objective evolutionary in implicit chemical spacecited by 1
  10. 2023Improving Performance Insensitivity of Large-scale Multiobjective Optimization via Monte Carlo Tree Searchcited by 1
  11. 2023Experience-Based Evolutionary Algorithms for Expensive Optimizationcited by 1
  12. 2023Rank-Based Learning and Local Model Based Evolutionary Algorithm for High-Dimensional Expensive Multi-Objective Problemscited by 1
  13. 2023Enhancing SAEAs with Unevaluated Solutions: A Case Study of Relation Model for Expensive Optimizationcited by 1
  14. 2025EvoRL: A GPU-accelerated Framework for Evolutionary Reinforcement Learningcited by 1
  15. 2025PlatMetaX: An Integrated MATLAB platform for Meta-Black-Box Optimizationcited by 1
  16. 2021Variable Division and Optimization for Constrained Multiobjective Portfolio Problemscited by 0
  17. 2021PAMELI: A Meta-Algorithm for Computationally Expensive Multi-Objective Optimization Problemscited by 0
  18. 2021Solving Large-Scale Multi-Objective Optimization via Probabilistic Prediction Modelcited by 0
  19. 2022A collaborative decomposition-based evolutionary algorithm integrating normal and penalty-based boundary intersection for many-objective optimizationcited by 0
  20. 2023ATM-R: An Adaptive Tradeoff Model with Reference Points for Constrained Multiobjective Evolutionary Optimizationcited by 0
  21. 2023Efficiently Tackling Million-Dimensional Multiobjective Problems: A Direction Sampling and Fine-Tuning Approachcited by 0
  22. 2023A Comparative Visual Analytics Framework for Evaluating Evolutionary Processes in Multi-objective Optimizationcited by 0
  23. 2024Analyzing and Overcoming Local Optima in Complex Multi-Objective Optimization by Decomposition-Based Evolutionary Algorithmscited by 0
  24. 2024A Multi-objective Optimization Benchmark Test Suite for Real-time Semantic Segmentationcited by 0
  25. 2024Multi-task multi-constraint differential evolution with elite-guided knowledge transfer for coal mine integrated energy system dispatchingcited by 0
  26. 2025ParetoLens: A Visual Analytics Framework for Exploring Solution Sets of Multi-objective Evolutionary Algorithmscited by 0
  27. 2025SEvoBench : A C++ Framework For Evolutionary Single-Objective Optimization Benchmarkingcited by 0
  28. 2025Maximum Dispersion, Maximum Concentration: Enhancing the Quality of MOP Solutionscited by 0
  29. 2026A Novel Immune Algorithm for Multiparty Multiobjective Optimizationcited by 0