Multiobjective optimization of the continuous casting process for poly (methyl methacrylate) using adapted genetic algorithm

The nondominated sorting genetic algorithm (NSGA) has been used to optimize the operation of the continuous casting of a film of poly (methyl methacry late). This process involves two reactors, namely, an isothermal plug flow tubular reactor (PFTR) followed by a nonisothermal film reactor. Two object ive functions have been used in this study: the cross-section average value of the monomer conversion, (x) over bar(mf), of the product is maximized, and the length, z(f), of the film reactor is minimized. Simultaneously, the cross-section average value of the number-average molecular weight of the product is forced to have a certain prescribed (desired) value. It is also ensured that the temperature at any location in the film being produced lie s below a certain value, to avoid degradation reactions. Seven decision var iables are used in this study: the temperature of the isothermal PFTR, the flow rate of the initiator in the feed to the PFTR (for a specified feed fl ow rate of the monomer), the film thickness, the monomer conversion at the output of the PFTR, and three coefficients describing the wall temperature to be used in the film reactor. Sets of nondominating (equally good) optima l solutions (Pareto sets) have been obtained due to the conflicting require ments for the several conditions studied. It is interesting to observe that under optimal conditions, the exothermicity of the reactions drives them t o completion near the center of the film, while heat conduction and higher wall temperature help to achieve this in the outer regions. (C) 2000 John W iley & Sons, Inc.