Multiobjective optimization of an industrial styrene reactor

The paper describes a multiobjective optimization study for industrial styrene reactors using non-dominated sorting genetic algorithm (NSGA). Several two- and three- objective functions, namely, production, yield and selectivity of styrene, are considered for adiabatic as well as steam-injected styrene reactors. Pareto optimal (a set of equally good) solutions are obtained due to conflicting effect of either ethyl benzene feed temperature or flow rate. The results provide extensive range of optimal operating conditions, from which a suitable operating point can be selected based on the specific requirements in the plant. (C) 2002 Elsevier Science Ltd. All rights reserved.