Multiobjective optimization of a free radical bulk polymerization reactor using genetic algorithm

A multiobjective optimization technique has been developed for free radical bulk polymerization reactors using genetic algorithm. The polymerization o f methyl methacrylate in a batch reactor has been studied as an example. Th e two objective functions which are minimized are the total reaction time a nd the polydispersity index of the polymer product. Simultaneously, end-poi nt constraints are incorporated to attain desired values of the monomer con version (x(m)) and the number average chain length (mu(n)). A nondominated sorting genetic algorithm (NSGA) has been adapted to obtain the optimal con trol variable (temperature) history. It has been shown that the optimal sol ution converges to a unique point and no Pareto set is obtained. It has bee n observed that the optimal solution obtained using the NSGA for multiobjec tive function optimization compares very well with the solution obtained us ing the simple genetic algorithm (SGA) for a single objective function opti mization problem, in which only the total reaction time is minimized and th e two endpoint constraints on x(m) and mu(n) are satisfied.