Multiobjective optimization of simulated moving bed and Varicol processes using a genetic algorithm

The size of the packing material, the total number of columns and the total feed concentration have significant impacts on the economics of a preparative chromatographic separation, through their effects on column pressure drop, column efficiency and thermodynamics. In this work, the role of these parameters on the performances of a simulated moving bed and a Varicol process is investigated on a chiral separation system from literature, using an equilibrium stage model. A multiple objective optimization technique based on a genetic algorithm is adopted, which allows to maximize simultaneously the purity of the extract and productivity of the unit. In this way, it is possible to optimize and compare the performances of both processes in a wide range of parameter values, so as to assess their relative potential under equally optimized conditions. The optimization results, i.e. the so-called Pareto sets, have been discussed in the frame of equilibrium theory and the roles of these three parameters have been clarified. [Copyright &y& Elsevier]