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Article . 2014 . Peer-reviewed
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The one‐dimensional cutting stock problem with sequence‐dependent cut losses

The one-dimensional cutting stock problem with sequence-dependent cut losses
Authors: Garraffa, Michele; Vancroonenburg, Wim; Salassa, Fabio; Vanden Berghe, Greet; Wauters, Tony;

The one‐dimensional cutting stock problem with sequence‐dependent cut losses

Abstract

AbstractThe paper presents a new generalization of the one‐dimensional cutting stock problem (1D‐CSP) that considers cut losses dependent on the items' cutting sequence. It is shown that this generalization can still be solved approximately by standard 1D‐CSP approaches. Furthermore, a pattern‐based heuristic (denoted by HSD) is presented that specifically considers sequence‐dependent cut losses (SDCL). A computational study shows that whenever some variability in SDCL occurs, consideration of SDCL in the HSD heuristic is beneficial. Finally, two case studies illustrate the relevance of this new generalization.

Countries
Italy, Belgium
Keywords

Technology, Combinatorial optimization, sequence-dependent cut losses, BIN-PACKING, Social Sciences, 3509 Transportation, logistics and supply chains, sequence dependent cut losses, itec, Business & Economics, 0102 Applied Mathematics, pattern based heuristic, 4901 Applied mathematics, TYPOLOGY, integer programming, cutting stock, Cutting stock, Science & Technology, Operations Research & Management Science, Integer programming, Approximation methods and heuristics in mathematical programming, pattern-based heuristic, Cutting Stock Problem; Integer Programming; Sequence-Dependent Cut Losses; Column Generation Heuristics; Matheuristics, Management, PACKING PROBLEMS, iMinds, 0806 Information Systems, 1503 Business and Management, TRAVELING SALESMAN PROBLEM

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Top 10%
Average
Green