MTO-Platform (MToP) is a comprehensive MATLAB benchmarking platform for evolutionary multitasking (EMT). It provides a unified, extensible framework for defining optimization problems, implementing algorithms, and evaluating performance metrics. The platform includes over 50 multitask algorithms (e.g., MFEA, AT-MFEA, TRADE, SSLT), 200+ multitask problem cases (including CEC, WCCI, and real-world benchmarks), and 20+ performance metrics (IGD, HV, Spread, etc.). It supports single-task, multi-task, many-task, multi-objective, constrained, and competitive optimization scenarios. The system features both a graphical user interface (GUI) and a command-line interface, with parallel execution support and integration with external tools like IOHanalyzer and Python Gym environments for policy search. The architecture is modular: base classes (Problem, Algorithm, Metric) define consistent interfaces, and all components inherit from them. Utility modules (Individual, Initialization, Selection, Operator, Multi-objective sorting) are shared across algorithms, promoting code reuse. The codebase also includes real-world applications such as global trajectory optimization, optimal power flow, sensor coverage, and photovoltaic model parameter extraction. While primarily a research platform, it also serves as a library of reusable evolutionary computation components. The repository is actively maintained (v1.10, references to 2026) but exhibits some technical drift: use of deprecated MATLAB functions (textread), large vendored third-party code (SOM Toolbox), and binary .mat files that may cause compatibility issues. Code duplication exists in problem definitions and some algorithm utilities. Despite these issues, the platform is well-structured, extensively documented, and widely cited in the EMT literature.
SimART is an open-source simulation platform for wireless communication and sensing research, integrating ray-tracing (Sionna RT), 3D visualization (VTK/Qt), drone simulation (AirSim/Unreal Engine), and ROS1 for data streaming. The system provides a desktop GUI (C++/Qt5) that loads 3D scenes from files, OpenStreetMap, or AirSim, and orchestrates real-time or offline radio propagation simulations. It generates channel knowledge maps (CKMs), beam codebooks, and system-level metrics (SINR, BLER, MCS), and supports machine learning-based beam selection via a DeepSense predictor. The platform is designed for researchers prototyping algorithms for UAV communications, beamforming, and link adaptation. While the codebase is functionally rich and modular in parts (scene providers, transform manager, socket workers), it suffers from significant technical drift: it depends on ROS1 (end-of-life), Unreal Engine 4.27 (discontinued), Qt5, and legacy VTK APIs. The C++ code contains large monolithic files (e.g., OsmSceneProvider.cpp ~1100 lines) and duplication between C++ and Python transform logic. There are no automated tests, and many configuration files lack schema validation. Despite these issues, several components (blender scripts, beam codebook utilities, scene provider interface) are well-isolated and could be reused in other projects with minimal adaptation.