A progressive heuristic search algorithm for the cutting stock problem

Abstract

This paper presents a new variant of the A* class algorithms for solving the known ‘one-dimensional cutting stock problem’ in a cardboard factory where the objective is to minimise the useless remaining of a continuous cardboard surface. The algorithm limits the number of nodes in the tree search by using a bound criterion based on the problem restrictions. The process of computing the solution is achieved at several stages, obtaining a complete non-optimal solution at each stage and improving the response as long as new stages are executed. The final stage returns the optimal solution. The proposed approach allows for a solution at anytime in the process resolution and also the refinement of the solution as more time is given to the algorithm. In this way, if a non-optimal solution is satisfactory enough for the factory, the process can be interrupted at that time. The computational performance of the algorithm indicates the effectiveness of the algorithm for solving practical one-dimensional cutting stock problems. Additionally, the experimental results show the important money savings achieved for the factory.KeywordsTime ExecutionTree SearchRoll WidthAlive NodeRoll LengthThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.