2011
DOI: 10.1016/j.ejor.2011.04.017
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The multiple container loading cost minimization problem

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Cited by 48 publications
(30 citation statements)
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“…This set cover formulation was first proposed by Eley (2003) and later employed by Che et al (2011). The set cover formulation for both 1D and 2D bin packing problem has also been proposed by Monaci and Toth (2006).…”
Section: Set Cover Formulation For the Mclcmpmentioning
confidence: 98%
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“…This set cover formulation was first proposed by Eley (2003) and later employed by Che et al (2011). The set cover formulation for both 1D and 2D bin packing problem has also been proposed by Monaci and Toth (2006).…”
Section: Set Cover Formulation For the Mclcmpmentioning
confidence: 98%
“…The author first generated packing patterns using a tree search based heuristic, then used a set cover formulation for linear integer programming using pregenerated packing patterns. Che et al (2011) adapted this set cover formulation by adding a loading factor parameter to exploit the excess capacity of the chosen containers, used three fast heuristic strategies to generate packing patterns, and performed a binary search on the loading factor. Zhu, Huang, et al (2012) presented a PCG strategy for this problem to speed up the process of column generation.…”
Section: Literature Reviewmentioning
confidence: 99%
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“…width and length of the rectangular pieces to be cut out. As expected, this problem is harder to solve than the one or two-dimensional palletloading problems [3][4][5].…”
Section: Introductionmentioning
confidence: 99%
“…Other papers also proposed solution techniques for similar problems, such as the Cutting Stock Problem in which there are only a few types of boxes (e.g. Brunetta and Gregoire (2005); Che et al (2011)), or also the Single Knapsack Problem in which there is only one bin to fill with a selection of items (e.g. Ngoi et al (1994) ;Hemminki July 11, 2017 International Journal of Production Research mipbasedheuristics et al (1998)).…”
Section: Introductionmentioning
confidence: 99%