Conference Agenda

Cutting stock problems are still considered within the class of NP-hard problems that continue to be actively studied in the field of combinatorial optimization. These problems encompass processes such as material utilization and waste generation, and their effective resolution plays a crucial role in managing operations that directly influence efficiency. From a sustainability perspective, the reduction of unused waste directly contributes to lowering environmental impacts, while improvements in material utilization enhance supply chain resilience by reducing dependency on raw material inputs. Consequently, unnecessary waste, overproduction, excessive ordering, and redundant transportation processes can be effectively minimized. Therefore, these problems are of significant importance in the context of sustainable manufacturing and logistics.

This study addresses a variant of the two-dimensional cutting stock problem with the objective of improving material efficiency within supply chains. The proposed approach is developed based on benchmark instances in literature.

While existing benchmark studies predominantly focus on two-stage and three-stage guillotine cutting strategies, this study expands the solution space by investigating randomized non-guillotine cutting patterns that eliminate traditional guillotine constraints. A mixed-integer goal programming model is formulated with the dual objectives of minimizing total material usage (objective cost) and maximizing the recoverable leftover area (leftover value). The proposed methodology aims to generate cutting patterns at an optimal level by integrating an evaluation framework that simultaneously considers minimal waste and maximum recovery potential.

Computational experiments were conducted, and the obtained results were systematically compared with those reported in the literature. The findings indicate that the proposed non-guillotine approach achieves superior performance, yielding lower objective costs and higher reusable leftover values compared to prior studies. In particular, it is observed that in cases where guillotine constraints restrict pattern diversity, the non-guillotine strategy provides a significant advantage by enabling more flexible and efficient cutting configurations.

Overall, this study contributes to the literature by demonstrating that relaxing structural cutting constraints can lead to both economic and environmental benefits. Furthermore, it provides a robust decision-support framework for practitioners seeking to optimize cutting operations under sustainability and resilience considerations.