This document introduces a set of 24 box-constrained numerical global optimization problem instances, systematically constructed using the Generalized Numerical Benchmark Generator (GNBG). These instances cover a broad spectrum of problem features, including varying degrees of modality, ruggedness, symmetry, conditioning, variable interaction structures, basin linearity, and deceptiveness. Purposefully designed, this test suite offers varying difficulty levels and problem characteristics, facilitating rigorous evaluation and comparative analysis of optimization algorithms. By presenting these problems, we aim to provide researchers with a structured platform to assess the strengths and weaknesses of their algorithms against challenges with known, controlled characteristics. For reproducibility, the MATLAB source code for this test suite is publicly available.

翻译：本文介绍了一组24个箱约束数值全局优化问题实例，这些实例利用广义数值基准生成器（GNBG）系统构建而成。该测试集涵盖了广泛的問題特征，包括不同程度的模态性、粗糙度、对称性、条件数、变量交互结构、盆地形线性度以及欺骗性。该测试集经过专门设计，提供了不同难度级别和问题特征，便于对优化算法进行严格评估与比较分析。通过呈现这些问题，我们旨在为研究人员提供一个结构化平台，使其能够评估算法在面对已知且可控特征挑战时的优势与不足。为确保可重复性，本测试集的MATLAB源代码已公开提供。