As model based optimization techniques play a more and more important role in the chemical process industries, there is a great demand for ever more efficient and reliable process optimization software. In the first part of this paper, the theoretical aspects of a tailored multiple shooting based solution strategy for dynamic process optimization have been presented (Leineweber, Bauer, Bock & Schloder, 2002. An efficient multiple shooting based reduced SQP strategy for large-scale dynamic process optimization-part 1: theoretical aspects). The current second part describes software aspects of the specific implementation muscod-ii and provides numerical results for several application examples. muscod-ii has been coupled with the dynamic process modeling software gPROMS via the standard equation set object (ESO) interface of CAPE-OPEN. Thereby, an advanced dynamic optimization platform for integrated batch processes has been created, where each process stage is separately modeled in gPROMS, and the multistage dynamic optimization problem is assembled and solved with MUSCOD-II. The code has also been parallelized. based on the portable MPI standard. It is shown that the use of directional sensitivities becomes very important for larger problems with many algebraic variables, leading to drastically reduced computing times compared with strategies with complete constraint linearization. In addition, gPROMS ESO models are compared with classical Fortran models in terms of computational performance, and it is found that only a moderate loss of performance occurs if so-called in-process ESOs are employed. Finally, it is demonstrated that a significant speed-up can be obtained through parallel function and gradient evaluations.