Vittorio Maniezzo

Stack Warehouse Management
The thesis, in collaboration with a company, requires the analysis and prototyping of a data science / operational analytics solution that optimizes the identification of product storage locations, both by implementing internal reordering logics ("reshuffle") and by proposing the storage location of pallets exiting the production plant on the basis of the stock status, the expected size of the production lot and of the sales forecast.


Scheduling logistic missions inside a warehouse
The thesis, in collaboration with a company, requires the analysis and prototyping of a data science / operational analytics solution that, starting from the study of historical data on the dispatch of tasks for the movement of logistical resources in the warehouse, arrives at defining task sequencing policies to optimize appropriate operational metrics (e.g., to minimize distances covered with unloaded forklifts).