OptimSuite

OptimSuite是一个综合性的基准套件，用于机器学习的黑盒优化，由法国巴黎的Facebook AI Research创建。该数据集涵盖了从学术基准到实际应用的广泛优化问题，包括离散、数值和混合整数问题，从小规模到大规模问题，从噪声到动态问题等。OptimSuite通过集成多个贡献，如LSGO、YABBOB、Pyomo、MLDA和MuJoCo等，提高了黑盒优化基准的可靠性和泛化性。该数据集的应用领域旨在解决算法选择和配置的问题，通过提供一个广泛的基准集合来支持自动化算法选择和配置，从而减少手动选择带来的偏差。

OptimSuite is a comprehensive benchmark suite for black-box optimization in machine learning, developed by Facebook AI Research in Paris, France. It encompasses a broad spectrum of optimization problems spanning academic benchmarks to real-world applications, including discrete, numerical, and mixed-integer problems, covering scales from small to large, as well as noisy and dynamic optimization tasks. By integrating multiple established resources such as LSGO, YABBOB, Pyomo, MLDA, and MuJoCo, OptimSuite enhances the reliability and generalizability of black-box optimization benchmarks. This suite targets the resolution of algorithm selection and configuration problems: it provides a diverse benchmark collection to support automated algorithm selection and configuration, thereby mitigating biases arising from manual selection.