An Improved Arcflow Model for the Skiving Stock Problem

John Martinovic (), Maxence Delorme (), Manuel Iori () and Guntram Scheithauer ()
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John Martinovic: Technische Universität Dresden
Maxence Delorme: The University of Edinburgh
Manuel Iori: Università di Modena e Reggio Emilia
Guntram Scheithauer: Technische Universität Dresden

A chapter in Operations Research Proceedings 2018, 2019, pp 135-141 from Springer

Abstract: 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.

Keywords: Cutting and packing; Skiving stock problem; Arcflow model; ILP (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-030-18500-8_18

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DOI: 10.1007/978-3-030-18500-8_18

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