The Bin Packing Problem (BPP) is a well-studied problem in Operations Research, and, in its basic formulation, it aims at packing a set of items into a finite set of bins by minimizing the number of used bins. Due to its wide range of applications, several variants of the problem have been proposed during the last decades, which differ from each other by dimensionality, additional constraints, and characteristics of the items or the bins. 

We consider a Two-Dimensional Bin Packing Problem (2DBPP) arising in Salvagnini Italia, a multinational corporation working in the sheet metal industry. In our problem, the basic 2DBPP is enriched by the presence of technological constraints emerging from the context, such as precedence relations between groups of items and conditional safety distances between items. We present exact and heuristic approaches to solve the problem, both based on Mixed Integer Linear Programming (MILP), and we show related computational results.