The optimization of distillation columns is critically important due to their substantial contribution to operational costs in the petrochemical industry. This paper introduces a computationally efficient surrogate-based optimization framework designed explicitly for prefractionation columns. To address the challenges of high computational cost and model accuracy in model-based optimization, a self-adaptive Kriging model, which features automated hyperparameter tuning via Bayesian optimization, is implemented and …