Model-based dynamic optimization is an effective tool for control and optimization of chemical processes, especially during transitions in operation. This study considers the dynamic optimization of load transitions. Poor operating point transition strategy can increase the quantity of off-spec product coming with financial loss, and also can increase the risk of malfunctions. A novel methodology for operating point transition optimization is applied to a vacuum distillation column unit in which concentration of cumene-hydroperoxide intermediate occurs. Optimization task is based on Open Platform Communication (OPC) between a commercial process simulator (Aspen HYSYS) and MATLAB. Nonlinear Optimization with Mesh Adaptive Direct Search algorithm (NOMAD) is applied to solve the task. Load of the distillation column is decreased from 100% to 90% taking into account the time of transition, amount of off-spec product and energy consumption. Different objective functions result definitely different transition strategies, therefore the right choice of this function is crucial step in this process. The results show that the proposed optimization methodology can be applied efficiently based on a complex simulator of the technology.