Abstract
The paper addresses the multiobjective optimization of a simulated moving-bed chromatographic reactor (SCMCR). The selection of the operating parameters such as the length and number of columns, switching time, and liquid flow rates in different sections is not straightforward in an SCMCR. In most cases, conflicting requirements and constraints govern the optimal choice of the decision (operating or design) variables. A mathematical model that predicts single-column experimental results well was modified for MTBE synthesis in an SCMCR. Thereafter, a few simple multiobjective optimization problems were solved that included both existing and designstage SCMCRs using a nondominated sorting genetic algorithm (NSGA). Optimal design and operating conditions for three cases of practical relevance are studied in this work, namely, (a) simultaneous maximization of the purity and yield of MTBE; (b) simultaneous maximization of the purity and yield of MTBE, together with minimization of the total amount of adsorbent/ catalyst required; and (c) maximization of the purity of MTBE with simultaneous minimization of the eluent consumption, to illustrate the procedures and interpret the results obtained. Paretooptimal solutions were obtained in all cases, and moreover, it was found that the performance of the SCMCR could be improved significantly under optimal operating conditions.
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