PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization
Ye Tian, Ran Cheng, Xingyi Zhang, Yaochu Jin

TL;DR
PlatEMO is an open-source MATLAB platform that provides a comprehensive environment with over 50 algorithms and 100 test problems for benchmarking and developing evolutionary multi-objective optimization methods.
Contribution
The paper introduces PlatEMO, a user-friendly, comprehensive, and open-source MATLAB platform for evolutionary multi-objective optimization research and application.
Findings
Includes 50+ algorithms and 100+ test problems
Enables easy comparison and statistical analysis
Supports development of new algorithms and test problems
Abstract
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…
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Taxonomy
TopicsAdvanced Multi-Objective Optimization Algorithms · Metaheuristic Optimization Algorithms Research · Evolutionary Algorithms and Applications
