A supply chain waste reduction optimization model using beam search algorithms for two-dimensional cutting problems with defects

Sustainability in supply chain management addresses various challenges, from waste minimization to resource efficiency maximization. Two-dimensional cutting problems are common problems in most supply chains where small rectangular items need to be cut from large rectangular stock sheets to meet production needs or customer demands. The large stock sheets, produced from materials such as paper, steel, or wood, often contain defects. An optimal cutting solution is needed to avoid overlap with any defects and minimize waste in the cutting process. We propose a supply chain waste reduction optimization model using beam search algorithms for two-dimensional cutting problems with defects. Our proposed solution leverages the power of advanced analytics through a dynamic programming approach. Our algorithms feature variable beam widths and heuristic rules to reduce computation times while yielding high-quality solutions. A simulation model is used to assess the performance of the proposed algorithms.