In the context of the project “SustMultBiomass”, founded by Horizon 2020, I will be running a python-based multi-objective optimizer to determine the optimal forest management treatment in >30.000 National Forest Inventory (NFI) plots. The input data is represented by three large databases (>50 GB) from the decision support system Heureka. These databases contains the estimated evolution of the forest stands for the next 100 years, when a certain management treatment is applied. The optimizer selects the best treatment in each plot in order to achieve the desired objectives. The objectives and the constraints for the optimization will be specified in a graphic user interface (GUI) built in a Jupiter Notebook.