Performance of two heuristics for solving large scale two-dimensional guillotine cutting problems

The two dimensional cutting problem consists of cutting a rectangular plate into specified smaller rectangular pieces, so that an objective function is optimized (for example, minimizing the waste). Different approaches and constraints for this problem have been considered by a number of authors. In particular, the unconstrained non-staged two-dimensional guillotine cutting problem was studied by Beasley, who proposed a heuristic to handle large problems, that is, problems with a large number of possible cutting patterns. It is also possible to deal with large problems by imposing an artificial constraint of limiting the cuts to two stages. In this paper the authors consider both approaches, comparing their performance with some randomly generated examples.