An Efficient Ant Colony Optimization for Two-dimensional Bin Packing Problem with Defect Issue

In various industries, manufacturers must cut rectangular items from stock sheets. In the actual setting, stock sheets inevitably contain some defects, and manufacturers have to avoid cutting the products which contain the defects (i.e., TFT?LCD industry, e-paper); therefore, the two-dimensional bin packing problems with defect (2DBPPWD) emerges. However, no effective method for solving 2DBPPWD in the current literature has been developed. To address the research gaps and industrial requirements, this study proposes an effective approach that integrates ant colony optimization with the flawless corner space placement algorithm to solve 2DBPPWD. Finally, we compare the proposed approach with the traditional approach (genetic algorithm integrated with bottom?left placement) to solve C21 (Hopper &Turton, 2001) and N13 (Burke et al., 2004) problems. Computational results demonstrate that our proposed approach can solve 2DBPPWD effectively and significantly outperform those of current approaches.