Version 1
: Received: 29 July 2024 / Approved: 29 July 2024 / Online: 30 July 2024 (07:25:19 CEST)
How to cite:
Barragan-Vite, I.; Medina-Marin, J.; Hernandez-Romero, N.; Anaya-Fuentes, G. E. A Petri Net-based Algorithm for Solving the One-Dimensional Cutting Stock Problem. Preprints2024, 2024072374. https://doi.org/10.20944/preprints202407.2374.v1
Barragan-Vite, I.; Medina-Marin, J.; Hernandez-Romero, N.; Anaya-Fuentes, G. E. A Petri Net-based Algorithm for Solving the One-Dimensional Cutting Stock Problem. Preprints 2024, 2024072374. https://doi.org/10.20944/preprints202407.2374.v1
Barragan-Vite, I.; Medina-Marin, J.; Hernandez-Romero, N.; Anaya-Fuentes, G. E. A Petri Net-based Algorithm for Solving the One-Dimensional Cutting Stock Problem. Preprints2024, 2024072374. https://doi.org/10.20944/preprints202407.2374.v1
APA Style
Barragan-Vite, I., Medina-Marin, J., Hernandez-Romero, N., & Anaya-Fuentes, G. E. (2024). A Petri Net-based Algorithm for Solving the One-Dimensional Cutting Stock Problem. Preprints. https://doi.org/10.20944/preprints202407.2374.v1
Chicago/Turabian Style
Barragan-Vite, I., Norberto Hernandez-Romero and Gustavo Erick Anaya-Fuentes. 2024 "A Petri Net-based Algorithm for Solving the One-Dimensional Cutting Stock Problem" Preprints. https://doi.org/10.20944/preprints202407.2374.v1
Abstract
Cutting and packing problems have been studied for decades and are of concern for a wide variety of industries to reduce costs and material utilization. This paper addresses the one-dimensional cutting stock problem, focusing on minimizing total stock usage. Procedures that address this problem include linear programming methods and metaheuristics. However, linear programming methods are limited to low-complexity instances, while most metaheuristics require extensive parameter tuning. In this paper, we develop a Petri-net model to construct cutting patterns. Using the reachability tree of the Petri net, the filtered beam search algorithm is implemented to find the best solution. Our algorithm is compared with the Least Lost Algorithm and the Generate & Solve algorithm over five datasets of instances. These algorithms share some characteristics with ours and have proven to be effective and efficient. Experimental results demonstrate that our algorithm effectively finds optimal solutions for both low and high-complexity instances. These findings confirm that Petri nets are suitable for modeling and solving the one-dimensional cutting stock problem.
Keywords
Cutting problem; packing problem; Petri net; reachability tree; beam search
Subject
Engineering, Industrial and Manufacturing Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
