The paper introduces PlatEMO, a MATLAB-based platform for evolutionary multi-objective optimization (EMO). PlatEMO aims to address the lack of a comprehensive and up-to-date software platform for benchmarking and applying EMO algorithms. It includes over 50 multi-objective evolutionary algorithms (MOEAs), more than 100 multi-objective test problems, and several performance indicators. The platform features a user-friendly graphical user interface (GUI) that allows users to compare multiple algorithms simultaneously and save results in Excel or LaTeX files. PlatEMO is open-source, enabling users to develop new algorithms and extend the platform. The paper details the architecture of PlatEMO, including its file structure, class diagram, and sequence diagram. It also explains how to run PlatEMO with and without the GUI, and provides instructions for extending the platform with new algorithms, problems, operators, and performance indicators. The authors plan to continuously maintain and develop PlatEMO, adding more state-of-the-art algorithms and features to enhance its functionality and usability.The paper introduces PlatEMO, a MATLAB-based platform for evolutionary multi-objective optimization (EMO). PlatEMO aims to address the lack of a comprehensive and up-to-date software platform for benchmarking and applying EMO algorithms. It includes over 50 multi-objective evolutionary algorithms (MOEAs), more than 100 multi-objective test problems, and several performance indicators. The platform features a user-friendly graphical user interface (GUI) that allows users to compare multiple algorithms simultaneously and save results in Excel or LaTeX files. PlatEMO is open-source, enabling users to develop new algorithms and extend the platform. The paper details the architecture of PlatEMO, including its file structure, class diagram, and sequence diagram. It also explains how to run PlatEMO with and without the GUI, and provides instructions for extending the platform with new algorithms, problems, operators, and performance indicators. The authors plan to continuously maintain and develop PlatEMO, adding more state-of-the-art algorithms and features to enhance its functionality and usability.