AI 中文总结
研究hMPA对CEC 2017变换的敏感性，引入参数化实现独立控制变换，通过DSC和eDSC进行配置级诊断，分析56个三配置子集，发现配置差异因函数而异，提供可重现诊断协议并可扩展。
AI 中文摘要
标准的CEC 2017基准同时应用偏差、偏移和旋转，混淆了它们对算法行为的个体影响。我们引入了一种参数化实现，可独立控制这些变换，同时保留原始函数和变换数据。该框架诊断混合海洋捕食者算法（hMPA），其预测候选机制依赖于数值目标值和坐标方向重建。DSC和扩展DSC（eDSC）从算法级比较改编为配置级诊断，首次对参数化CEC 2017基准的所有八种偏差 - 偏移 - 旋转配置进行详尽分析。我们检查了所有56个三配置子集，并与未变换的控制进行比较。实验涵盖29个函数，维度为10 - 100，30次独立运行，预算为10000 * 维度的目标函数评估次数。DSC和eDSC在每个维度都检测到配置之间具有统计学显著差异，但排名因函数而异，无法形成一致的排序。偏移通常会使目标值变差；孤立的旋转不会导致系统恶化，而孤立的偏差对最终解分布影响很小。偏移 - 旋转组合与控制的差异最为一致。收敛图揭示了函数和维度相关的分离、平稳期和后期改进。结果仅限于hMPA、所选参数、30次运行、固定预算以及分析的CEC 2017函数。在此范围内，该框架提供了可重现的诊断协议，可扩展到其他连续优化器和相关的CEC基准，包括CEC 2024和CEC 2025。
英文摘要
The standard CEC 2017 benchmark applies bias, shift, and rotation simultaneously, confounding their individual effects on algorithmic behavior. We introduce a parameterized implementation that controls these transformations independently while preserving the original functions and transformation data. The framework diagnoses the hybrid Marine Predators Algorithm (hMPA), whose predicted-candidate mechanism depends on numerical objective values and coordinate-wise reconstruction. DSC and extended DSC (eDSC) are adapted from algorithm-level comparison to configuration-level diagnosis, enabling, to our knowledge, the first exhaustive analysis of all eight bias-shift-rotation configurations of a parameterized CEC 2017 benchmark. We examine all 56 three-configuration subsets and comparisons with the untransformed control. Experiments cover 29 functions, dimensions 10-100, 30 independent runs, and a budget of 10000*dim objective-function evaluations. DSC and eDSC detect statistically significant differences among configurations at every dimension, but rankings vary across functions, preventing a consistent ordering. Shift generally worsens objective values; isolated rotation causes no systematic deterioration, while isolated bias has little effect on final-solution distributions. Shift-rotation combinations differ most consistently from the control. Convergence plots reveal function- and dimension-dependent separation, plateaus, and late improvement. Results are limited to hMPA, the chosen parameters, 30 runs, the fixed budget, and the analyzed CEC 2017 functions. Within this scope, the framework provides a reproducible diagnostic protocol extensible to other continuous optimizers and related CEC benchmarks, including CEC 2024 and CEC 2025.
