In the first part of this series [Ind. Eng. Chem. Res. 2006, 45, 7856-7866], data-driven approaches, based on partial least squares (PLS) models built from historical batch data, were used to find optimal batch operating trajectories that would yield a desired vector of final product quality attributes. The method allowed for the inclusion of univariate and multivariate constraints on the set of desired final product quality attributes and presented approaches for handling multiple solutions. In this paper, the technology is further extended to include constraints in the process operating trajectories themselves. The methodology is successfully applied to an industrial batch polymerization process where the batch trajectories are designed to achieve specific properties of the final polymer while consuming the minimal amount of time for the batch run.