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International Conference on AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems

CPAIOR 2017: Integration of AI and OR Techniques in Constraint Programming pp 293–301Cite as

Optimal Stock Sizing in a Cutting Stock Problem with Stochastic Demands

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10335))

Abstract

One dimensional cutting stock problems arise in many manufacturing domains such as pulp and paper, textile and wood. In this paper, a new real life variant of the problem occuring in the rubber mold industry is introduced. It integrates both operational and strategical planning optimization: on one side, items need to be cut out of stocks of different lengths while minimizing trim loss, excess of production and the number of required cutting operations. Demands are however stochastic therefore the strategic choice of which mold(s) to build (i.e. which stock lengths will be available) is key for the minimization of the operational costs. A deterministic pattern-based formulation and a two-stage stochastic problem are presented. The models developed are solved with a mixed integer programming solver supported by a constraint programming procedure to generate cutting patterns. The approach shows promising experimental results on a set of realistic industrial instances.

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Notes

  1. 1.

    For comparison, an item-based model was also developed; it showed quickly its limitations even in relatively small instances as soon as included the over production. For brevity, we omit the item-based model and results.

  2. 2.

    For comparison an equivalent MIP model was also developed, however it performed orders of magnitude slower for enumerating all the solutions.

  3. 3.

    This was the case in the real industrial context examined.

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Acknowledgements

The author would like to thank Davide Zanarini for bringing to his attention this industrial problem.

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Authors and Affiliations

  1. ABB Corporate Research Center, Baden-Dättwil, Switzerland

    Alessandro Zanarini

Authors
  1. Alessandro Zanarini
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Correspondence to Alessandro Zanarini .

Editor information

Editors and Affiliations

  1. University of Padua, Padua, Italy

    Domenico Salvagnin

  2. University of Bologna, Bologna, Italy

    Michele Lombardi

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Zanarini, A. (2017). Optimal Stock Sizing in a Cutting Stock Problem with Stochastic Demands. In: Salvagnin, D., Lombardi, M. (eds) Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2017. Lecture Notes in Computer Science(), vol 10335. Springer, Cham. https://doi.org/10.1007/978-3-319-59776-8_24

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  • DOI: https://doi.org/10.1007/978-3-319-59776-8_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59775-1

  • Online ISBN: 978-3-319-59776-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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