PlatMetaX: An Integrated MATLAB platform for Meta-Black-Box Optimization

• URL: http://arxiv.org/abs/2503.22722v1
• Date: Wed, 26 Mar 2025 02:03:35 GMT
• Title: PlatMetaX: An Integrated MATLAB platform for Meta-Black-Box Optimization
• Authors: Xu Yang, Rui Wang, Kaiwen Li, Wenhua Li, Tao Zhang, Fujun He,
• Abstract summary: We present PlatMetaX, a novel platform for developing, evaluating, and comparing optimization algorithms.<n>PlatMetaX integrates the strengths of MetaBox and PlatEMO, offering a comprehensive framework for developing, evaluating, and comparing optimization algorithms.
• Score: 13.141855165689448
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The landscape of optimization problems has become increasingly complex, necessitating the development of advanced optimization techniques. Meta-Black-Box Optimization (MetaBBO), which involves refining the optimization algorithms themselves via meta-learning, has emerged as a promising approach. Recognizing the limitations in existing platforms, we presents PlatMetaX, a novel MATLAB platform for MetaBBO with reinforcement learning. PlatMetaX integrates the strengths of MetaBox and PlatEMO, offering a comprehensive framework for developing, evaluating, and comparing optimization algorithms. The platform is designed to handle a wide range of optimization problems, from single-objective to multi-objective, and is equipped with a rich set of baseline algorithms and evaluation metrics. We demonstrate the utility of PlatMetaX through extensive experiments and provide insights into its design and implementation. PlatMetaX is available at: \href{https://github.com/Yxxx616/PlatMetaX}{https://github.com/Yxxx616/PlatMetaX}.

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