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A Variable Neighborhood Search Using Very Large Neighborhood Structures for the 3-Staged 2-Dimensional Cutting Stock Problem

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Hybrid Metaheuristics (HM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8457))

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Abstract

In this work we consider the 3-staged 2-dimensional cutting stock problem, which appears in many real-world applications such as glass and wood cutting and various scheduling tasks. We suggest a variable neighborhood search (VNS) employing “ruin-and-recreate”-based very large neighborhood searches (VLNS). We further present a polynomial-sized integer linear programming model (ILP) for solving the subproblem of 2-staged 2-dimensional cutting with variable sheet sizes, which is exploited in an additional neighborhood search within the VNS. Both methods yield significantly better results on about half of the benchmark instances from literature than have been published before.

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Authors and Affiliations

  1. Institute of Computer Graphics and Algorithms, Vienna Unviersity of Technology, Favoritenstr. 9/1861, 1040, Vienna, Austria

    Frederico Dusberger & Günther R. Raidl

Authors
  1. Frederico Dusberger
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  2. Günther R. Raidl
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Editor information

Editors and Affiliations

  1. Dept. Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya, Jordi Girona 1-3, edif. Omega, 08034, Barcelona, Spain

    Maria J. Blesa

  2. Dept. of Computer Science, IKERBASQUE and University of the Basque Country, Paseo Manuel Lardizabal 1, 20018, Donostia, Spain

    Christian Blum

  3. Dept. of Business and Informatics, University of Hamburg, Institute of Information Systems, Von-Melle-Park 5, 20146, Hamburg, Germany

    Stefan Voß

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© 2014 Springer International Publishing Switzerland

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Dusberger, F., Raidl, G.R. (2014). A Variable Neighborhood Search Using Very Large Neighborhood Structures for the 3-Staged 2-Dimensional Cutting Stock Problem. In: Blesa, M.J., Blum, C., Voß, S. (eds) Hybrid Metaheuristics. HM 2014. Lecture Notes in Computer Science, vol 8457. Springer, Cham. https://doi.org/10.1007/978-3-319-07644-7_7

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  • DOI: https://doi.org/10.1007/978-3-319-07644-7_7

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07643-0

  • Online ISBN: 978-3-319-07644-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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