Artikel
Improved layout structure with complexity measures for the Manufacturer's pallet loading problem (MPLP) using a Block approach
Purpose: The purpose of this paper is to study the Manufacturers pallet-loading problem (MPLP), by loading identical small boxes onto a rectangle pallet to maximise the pallet utilization percentage while reducing the Complexity of loading. Design/methodology/approach: In this research a Block approach is proposed using a Mixed integer linear programming (MILP) model that generates layouts of an improved structure, which is very effective due to its properties in grouping boxes in a certain orientation along the X and Y axis. Also, a novel complexity index is introduced to compare the complexity for different pallet loading, which have the same pallet size but different box arrangements. Findings: The proposed algorithm has been tested against available data-sets in literature and the complexity measure and graphical layout results clearly demonstrate the superiority of the proposed approach compared with literature Manufacturers pallet-loading problem layouts. Originality/value: This study aids real life manufactures operations when less complex operations are essential to reduce the complexity of pallet loading.
- Language
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Englisch
- Bibliographic citation
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Journal: Journal of Industrial Engineering and Management (JIEM) ; ISSN: 2013-0953 ; Volume: 14 ; Year: 2021 ; Issue: 2 ; Pages: 231-249 ; Barcelona: OmniaScience
- Classification
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Management
- Subject
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manufactures pallet loading problems
cutting and packing problems
mathematical programming
mixed integer optimization
- Event
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Geistige Schöpfung
- (who)
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Aljuhani, Deemah
Papageorgiou, Lazaros
- Event
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Veröffentlichung
- (who)
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OmniaScience
- (where)
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Barcelona
- (when)
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2021
- DOI
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doi:10.3926/jiem.3264
- Handle
- Last update
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10.03.2025, 11:42 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Aljuhani, Deemah
- Papageorgiou, Lazaros
- OmniaScience
Time of origin
- 2021