An efficient approach for large-scale two-dimensional guillotine cutting stock problems

We present an efficient method for solving approximately both constrained and unconstrained two-dimensional cutting stock problems. The algorithm guarantees a constant approximation ratio for some versions of the problem. The performance of the proposed is evaluated on several large-scale randomly generated problem instances and on many instances of the literature. Computational results show that our algorithm produces high-quality solutions within reasonable computational times.