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Tuning differential evolution algorithm for constructing uniform projection designs
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AI
DOI：10.1016/j.jspi.2025.106356.png)
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Abstract
En 中文
Space-filling designs are extensively used in computer experiments to analyze complex systems. Among these, uniform projection designs stand out for their desirable low-dimensional projection properties and robustness against other criteria. However, no efficient algorithm currently exists for generating such designs. This study explores the construction of uniform projection designs using a differential evolution (DE) algorithm. DE, an evolutionary algorithm, is known for its simplicity, robustness, and effectiveness in solving complex optimization problems, though its performance is highly sensitive to several hyperparameters. Our goal is to investigate the structure of the hyperparameter space, evaluate the contribution of each hyperparameter, and provide guidelines for optimal hyperparameter settings across various scenarios. To achieve this, we conduct a comprehensive comparison of different experimental designs and surrogate models.
Keywords:
Computer experiment
Experimental design
Hyperparameter optimization
Kriging model
Metaheuristic algorithm
Space-filling design
Journal
J
IF:
0.8
Papers:
38
Citations:
4.5K
