Our research focus is on a particular C&P problem commonly referred to as the irregular strip packing problem (ISPP).
Furthermore, according to the typology of , the ISPP has an open arbitrary dimension classification.
The approach proposed here was a parallel computing implementation of the Biased Random-Key Genetic Algorithm (BRKGA)  using multiple populations applied to an ISPP. Each solution develops a sequence in which the pieces are positioned in the container.
For our research, we adopted a Biased Random-Key Genetic Algorithm (BRKGA) applied with multiple parallel populations to tackle ISPP.
The ISPP demands a suitable geometrical representation when continuous rotations are necessary for a set of pieces.
In , the authors proposed a RKGA for ISPP and for the positioning method applied three constructive procedures to the polygonal representation of the pieces.
Furthermore, a BRKGA to ISPP was developed by , but in this work, the researches applied a BL heuristic to the positioning items and presented an NFP-raster at a grid model introduced by .