Uniform designs in constrained experimental domains based on the charge repulsion algorithm

Uniform design in constrained experimental domains (UDCED) poses significant challenges due to the complexity of constraints and high dimensionality. Although the advanced two-phase differential evolution (ToPDE) algorithm has shown improvements in search capabilities, it still suffers from low evolutionary efficiency and limited solution granularity. To address these limitations, this paper proposes the Charge Repulsion Algorithm (CRA), a novel algorithm specifically designed for uniform design in constrained experimental domains for UDCEDs. In CRA, sample points within the constrained domain are modeled as equal-mass spheres carrying identical charges. The algorithm leverages the physical principle that like-charged objects repel each other, thereby promoting uniform distribution by maximizing the minimum inter-point distance. To enhance global search performance, CRA integrates the iterative point deletion strategy from ToPDE and dynamically relocates sample points to sparser regions using the minimum distance (MD) criterion. This hybrid mechanism enables the algorithm to escape local optima and effectively handle complex constraints and high-dimensional search spaces. Experimental results demonstrate that CRA consistently outperforms ToPDE under both the MD and minimum distance maximization criteria, exhibiting superior solution quality and robustness.