A GPU-Accelerated Approach to Static Stability Assessments for Pallet Loading in Air Cargo

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dc.contributor.authorMazur, Philipp Gabriel
dc.contributor.authorLee, No-San
dc.contributor.authorSchoder, Detlef
dc.date.accessioned2021-12-24T17:31:47Z
dc.date.available2021-12-24T17:31:47Z
dc.date.issued2022-01-04
dc.description.abstractThe static stability constraint is one of the most important constraints in pallet loading and plays a substantial role when assembling safe and loadable palletizing layouts. Current approaches reach their limits as soon as additional complexity is added, which is a given in the practice of air cargo logistics, or when performance becomes important. As our central objective, we explore a new approach to calculate static stability more performantly and to cover more complexity by relaxing several simplifying assumptions. The approach is implemented in a prototype and builds on the emerging technology of graphical processing unit acceleration in combination with physics engines. We propose a new artifact design and summarize the how-to knowledge in the form of abstracted design principles. Our results demonstrate an improvement in terms of performance depending on the underlying hardware. We develop a conceptual model to assist future research in choosing a solution technology.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2022.204
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/79536
dc.language.isoeng
dc.relation.ispartofProceedings of the 55th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectIntelligent Decision Support for Logistics and Supply Chain Management
dc.subjectair cargo transportation
dc.subjectgpgpu
dc.subjectpallet loading
dc.subjectphysics engine
dc.subjectsimulation
dc.titleA GPU-Accelerated Approach to Static Stability Assessments for Pallet Loading in Air Cargo
dc.type.dcmitext

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