Abstract
We present a new scalable approach for the K-staged two-dimensional 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.
We thank LodeStar Technology for their support and collaboration in this project.
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Dusberger, F., Raidl, G.R. (2015). A Scalable Approach for the K-Staged Two-Dimensional Cutting Stock Problem with Variable Sheet Size. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2015. EUROCAST 2015. Lecture Notes in Computer Science(), vol 9520. Springer, Cham. https://doi.org/10.1007/978-3-319-27340-2_48
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DOI: https://doi.org/10.1007/978-3-319-27340-2_48
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