Using surrogate models for efficient optimization of simulated moving bed chromatography.

Highlights: [•] A new approach of using computationally cheap surrogate models for optimization of SMB chromatography is presented. [•] Two different types of surrogate models are developed to replace the detailed but expensive full-order SMB model for optimization. [•] The trust-region framework is proposed to implement an efficient and reliable management of both types of surrogates. [•] The results show that the new scheme not only converges to the optimum obtained with the full-order system, but also yields significant computational advantages. [Copyright &y& Elsevier]