A number of important chemical engineering processes are operated in a tran
sient manner (e.g., batch processes) and cannot be considered to reach a st
eady state. Optimizing the operations of such processes requires the soluti
on of a dynamic optimization problem, producing time-based trajectories for
process variables, A key characteristic of dynamic optimization problems i
s that the process model contains differential equations. Numerical solutio
n techniques, which are currently in widespread use, are usually based on d
iscretization schemes and can be computationally expensive. This paper prop
oses an alternative method for solving dynamic optimization problems in whi
ch the nonlinear process model is flat. The approach exploits, as appropria
te, either the differential flatness or the orbital flatness of the process
model to explicitly eliminate the differential equations from the optimiza
tion problem. The resulting optimization problem is solely algebraically co
nstrained and can be solved using readily available optimization codes. The
proposed approach is demonstrated on a range of benchmark problems taken f
rom the literature.