Extended Haessler Heuristic Algorithm for Cutting Stock Problem: a Case Study in Film Industry

The cutting stock problem is an important problem in the field of combinational optimization. In classic versions of this problem, the aim is to find a solution for cutting some equalwidth mother rolls into smaller parts with given width so that the amount of trim-loss become as small as possible. There are plenty of works which addressed the classic cutting stock problem. However in real world applications there are usually some constraints which make the problem different form classical version and make it harder to solve. In this paper we investigate a special cutting stock problem in film industry and show that it can not be solved by using previous methods. We propose a new hybrid method which combines previous methods and takes into account the constraints of this special problem. We applied our method on real data from a film production factory. The experiments show that our method can solve this problem efficiently and outperforms the previous methods.