The aim of this paper is to present a global approach to dynamic optimization of batch emulsion polymerization reactors using a stochastic optimizer. The objective is to minimize the final batch time with constraints on the final conversion and molecular weight, using the reactor temperature as the manipulated variable. First, results from the standard SQP-based approach are presented to illustrate how this problem is prone to be stuck in local minima. Then, in this study, the applicability of MSIMPSA, a simulated annealing-based algorithm, is evaluated. The results obtained are only marginally superior to those reported in the literature. However, the main outcomes of this study are: (i) MSIMPSA can be applied in an easy and straightforward manner to such optimal control problems. (ii) Though MSIMPSA is a stochastic algorithm, the best obtained solution is so good that it cannot be improved further by local optimization methods.