This paper deals with multi-objective optimization of styrene reactor using Tabu search (TS) and genetic algorithm (GA) methods. Styrene is produced commercially by catalytic dehydrogenation of ethyl benzene. As styrene is an important monomer, the capacity of the plant is usually very high, as a result the investment cost is also very high, and even a small enhancement in the plant operation can generate major income. The adiabatic reactor using the pseudo homogeneous model was considered in this study for maximizing the styrene conversion and selectivity. A computer program was written to simulate an adiabatic reactor in order to evaluate the possibility of optimizing the process in simulation environment. The simulation results were compared with the experimental data. This comparison indicated that the value of overall mean squarer of errors for conversion of the compounds was 7.09E-05 and overall means relative error of them was 2.18 percent. In order to optimize the performance of the reactors, conversion of styrene was adopted as the objective function. Six decision variables, namely, ethyl benzene feed temperature at the entrance of each bed, pressure, the ratio of steam to ethyl benzene and initial ethyl benzene flow rate were used for the optimization. The results of GA optimization showed final conversion of styrene increased from an initial value of 0.710 to 0.75 after 100 generation of population. Applying Tabu algorithm optimization, the value rose from 0.725 to 0.813 after generation of 100 neighborhoods. The results revealed that the CPU time needed to optimize the reactor for TS was shorter than that of GA method. In addition, using the same iteration numbers for both methods, the optimum value of styrene conversion was greater when TS method was applied.
©2012 Walter de Gruyter GmbH & Co. KG, Berlin/Boston