Research ArticleDynamic optimization of a copolymerization reactor using tabu search

- A novel multistage dynamic optimization method based on meta-heuristic tabu search(TS) is proposed.
- Its performance is evaluated by applying it to compute the optimal control policies of a semi-batch copolymerization reactor to achieve the desired product quality parameters.
- The simulation results demonstrate the usefulness of TS for optimal control of transient dynamic systems.

A novel multistage dynamic optimization strategy based on meta-heuristic tabu search (TS) is proposed and evaluated through sequential and simultaneous implementation procedures by applying it to a semi-batch styrene-acrylonitrile (SAN) copolymerization reactor. The adaptive memory and responsive exploration features of TS are exploited to design the dynamic optimization strategy and compute the optimal control policies for temperature and monomer addition rate so as to achieve the desired product quality parameters expressed in terms of single and multiple objectives. The dynamic optimization results of TS sequential and TS simultaneous implementation strategies are analyzed and compared with those of a conventional optimization technique based on iterative dynamic programming (IDP). The simulation results demonstrate the usefulness of TS for optimal control of transient dynamic systems.