Dynamic optimization of batch emulsion polymerization using MSIMPSA, a simulated-annealing-based algorithm

The aim of this paper is to present an approach to dynamic off-line optimization of batch emulsion polymerization reactors using a stochastic optimizer. The control objective is to find the optimal temperature profile that minimizes the final batch time constrained by the final conversion and molecular weight. In this study, we evaluate the applicability of MSIMPSA, a simulated-annealing-based algorithm, to solve the optimal control problem. Two cases are studied: first, a simple case without energy balances and, second, a more realistic case using energy balances and constraints on heat transfer. In addition, an SQP optimizer was applied to perform a local optimization around the best results obtained by MSIMPSA. The following conclusions can be drawn from the results: (i) MSIMPSA can be applied in an easy and straightforward manner (black-box approach) to such optimal control problems. (ii) Even though MSIMPSA is a stochastic algorithm, the best obtained solution is so good that it cannot be further improved by local optimization methods.