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An Improved Arcflow Model for the Skiving Stock Problem

In: Operations Research Proceedings 2018

Author

Listed:
  • John Martinovic

    (Technische Universität Dresden)

  • Maxence Delorme

    (The University of Edinburgh)

  • Manuel Iori

    (Università di Modena e Reggio Emilia)

  • Guntram Scheithauer

    (Technische Universität Dresden)

Abstract

Because of the sharp development of (commercial) MILP software and hardware components, pseudo-polynomial formulations have been established as a viable tool for solving cutting and packing problems in recent years. Constituting a natural (but independent) counterpart of the well-known cutting stock problem, the one-dimensional skiving stock problem (SSP) asks for the maximal number of large objects (specified by some threshold length) that can be obtained by recomposing a given inventory of smaller items. In this paper, we introduce a new arcflow formulation for the SSP applying the idea of reflected arcs. In particular, this new model is shown to possess significantly fewer variables as well as a better numerical performance compared to the standard arcflow formulation.

Suggested Citation

  • John Martinovic & Maxence Delorme & Manuel Iori & Guntram Scheithauer, 2019. "An Improved Arcflow Model for the Skiving Stock Problem," Operations Research Proceedings, in: Bernard Fortz & Martine Labbé (ed.), Operations Research Proceedings 2018, pages 135-141, Springer.
    • Handle: RePEc:spr:oprchp:978-3-030-18500-8_18
    DOI: 10.1007/978-3-030-18500-8_18
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