A novel approach for reactor network synthesis using knowledge discovery and optimization techniques

We present a novel framework for the optimization and synthesis of complex reactor networks based on systems knowledge in an effort to overcome convergence and computational speed limitations associated with current reactor network synthesis technologies. Reaction pathway analysis uses data mining techniques for knowledge acquisition to develop design rules which are subsequently used to focus superstructure optimization using meta-heuristics in the form of tabu search. The paper focuses on the components of the framework and presents successful applications to previously studied reactor network optimization problems.