Large scale optimization strategies for zone configuration of simulated moving beds

Simulated moving bed (SMB) processes are widely used in sugar, petrochemical, and pharmaceutical industries. However, systematic optimization of SMB, especially finding the optimal zone configuration including the standard and modified non-standard configurations, is still a challenging problem. This paper proposes a simultaneous, fully discretized approach with an SMB superstructure using an interior-point solver. To find the optimal structure, two superstructures are analyzed to develop standard and non-standard configurations. In case studies of the linear and bi-Langmuir isotherms, optimal zone configurations have been successfully obtained without introducing discrete variables. Finally, the effect of the number of columns on the optimal throughput is investigated.