An integrated algorithm for cutting stock problems in the thin-film transistor liquid crystal display industry

The cutting stock problem (CSP) is a critical issue in the manufacturing of thin film transistor liquid crystal display (TFT-LCD) products. Two manufacturing processes are utilized in this industry: (1) various TFT-LCD plates are cut from a glass substrate based on cutting patterns, and (2) the number of glass substrates required to satisfy customer requirements is minimized. The current algorithm used to select the cutting pattern is defined as a mixed integer program (MIP). Although the current MIP method yields an optimal solution, but the computation time is unacceptable when the problem scale is large. To accelerate the computation and improve the current method, this study proposes an integrated algorithm that incorporates a genetic algorithm, a corner arrangement method, and a production plan model to solve CSPs in the TFT-LCD industry. The results of numerical experiments demonstrate that the proposed algorithm is significantly more efficient than the current method, especially when applied to large-scale problems.