A Novel Gaussian Process Surrogate Model with Expected Prediction Error for Optimization under Constraints
Optimization, particularly constrained optimization problems (COPs), is fundamental in engineering, influencing various sectors with its critical role in enhancing design efficiency, reducing experimental costs, and shortening testing cycles.This study explores read more the challenges inherent in COPs, with a focus on developing efficient solution