Reel and sheet cutting at a paper mill
Computers and Operations Research
A combined approach to the solution to the general one-dimensional cutting stock problem
Computers and Operations Research
A pattern generation-integer programming based formulation for the carpet loading problem
Computers and Industrial Engineering
Heuristic algorithm for a cutting stock problem in the steel bridge construction
Computers and Operations Research
Modern Floorplanning with Boundary Clustering Constraint
ISVLSI '09 Proceedings of the 2009 IEEE Computer Society Annual Symposium on VLSI
An optimization algorithm for cutting stock problems in the TFT-LCD industry
Computers and Industrial Engineering
A genetic algorithm for solving the two-dimensional assortment problem
Computers and Industrial Engineering
Algorithms for 3D guillotine cutting problems: Unbounded knapsack, cutting stock and strip packing
Computers and Operations Research
Hybrid heuristic algorithm for two-dimensional steel coil cutting problem
Computers and Industrial Engineering
A Memetic Algorithm for VLSI Floorplanning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Cutting stock optimization and integral production planning for centralized wood processing
Mathematical and Computer Modelling: An International Journal
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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.