A Scalable Approach for the K-Staged Two-Dimensional Cutting Stock Problem with Variable Sheet Size
نویسندگان
چکیده
We present a new scalable approach for the K-staged twodimensional cutting stock problem with variable sheet size, particularly aiming to solve large-scale instances from industry. A construction heuristic exploiting the congruency of subpatterns efficiently computes sheet patterns of high quality. This heuristic is embedded in a beam-search framework to allow for a meaningful selection from the available sheet types. Computational experiments on benchmark instances show the effectiveness of our approach and demonstrate its scalability.
منابع مشابه
A Scalable Approach for the K-Staged Two-Dimensional Cutting Stock Problem
This work focuses on the K-staged two-dimensional cutting stock problem with variable sheet size. High-quality solutions are computed by an efficient beam-search algorithm that exploits the congruency of subpatterns and takes informed decisions on which of the available sheet types to use for the solutions. We extend this algorithm by embedding it in a sequential value-correction framework that...
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