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Sensitivity of hMPA to Controlled CEC 2017 Transformations

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arXiv:2607.22862v1 Announce Type: new Abstract: 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 evaluat...

arXiv Neural/NEabout 4 hours ago
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Sensitivity of hMPA to Controlled CEC 2017 Transformations | Steek AI Signal | Steek