To achieve low tailpipe NOX emissions in Heavy-Duty engines, the rapid warm-up of the exhaust aftertreatment system (EAS) needs to be assisted by the adoption of new technologies to reduce engine-out emissions and increase the EAS conversion efficiency. Engine measures like cylinder deactivation, retarded start of the main injection, late intake valve closing, intake throttling and elevated idle speed can substantially increase the available exhaust gas enthalpy and temperature at the expense of additional fuel as has been shown in the literature. On the other hand, the exhaust system can be optimized in terms of hardware and controls, which is nowadays strongly supported by simulation. However, these simulation studies typically assume a fixed engine hardware and calibration and thus fixed engine-out simulation boundary conditions. Moving forward to tougher and real-world oriented legislation, the fixed cycle and engine-out boundary condition becomes insufficient. The present work proposes a model-based approach that covers both the engine and the aftertreatment system in a single simulation platform. To ensure the predictive nature of the simulation, all engine and aftertreatment models were calibrated with appropriate experimental techniques. The models are scalable depending on the application target; for most of the results of this work, we employ fast running 1d models. Using the holistic simulation approach, it is possible to virtually activate and optimize the settings of various engine parameters to obtain a good trade-off in terms of fuel penalty and tailpipe emissions. Due to the huge number of parameter combinations, the optimization process itself is a real challenge that is addressed in the present work and time-efficient workflows are demonstrated. The application cases presented emphasize on technologies expected to be relevant for upcoming legislation, including close-coupled SCR and active exhaust heating.