Configurations of a four-column simulated moving bed chromatographic process are investigated by multi-objective optimization. Various existing column configurations are compared through a multi-objective optimization problem. Furthermore, an approach based on an SMB superstructure is applied to find novel configurations which have been found to outperform the standard SMB configuration. An efficient numerical optimization technique is applied to the mathematical model of the SMB process. It has been confirmed that although the optimal configuration highly depends on the purity requirement, the superstructure approach is able to find the most efficient configuration without exploring various existing configurations.