Metamodel-based Simulation Optimization Using Machine Learning for Solving Production Planning Problems in the Automotive Industry

Simple item page
dc.contributor.authorSchweitzer, Felicia
dc.contributor.authorHabel, Lars
dc.contributor.authorCanaviri Vilca, Oscar Jhonny
dc.contributor.authorKulzer, Tobias
dc.contributor.authorWenzel, Sigrid
dc.date.accessioned2024-12-26T21:05:51Z
dc.date.available2024-12-26T21:05:51Z
dc.date.issued2025-01-07
dc.description.abstractDue to the rising complexity of production systems in the automotive industry, simulation has become an established tool for analyzing dynamic systems. However, once the number of parameter combinations rises exponentially, the generation and evaluation of all possible solutions gets impractical. While the combination of simulation and optimization has a long tradition in academic research, its adoption in the automotive industry remains limited, often due to the high execution time associated with optimization experiments. To enable more efficient decision- making, this paper explores the integration of machine learning and optimization for simulation optimization. Specifically, it focuses on the use of metamodels incorporating various machine learning algorithms and metaheuristics to optimize two production planning problems with multiple parameter classes. The presented approach enables decision-makers to conduct a rapid assessment of complex production systems.
dc.format.extent10
dc.identifier.doi10.24251/HICSS.2025.206
dc.identifier.isbn978-0-9981331-8-8
dc.identifier.othered923c80-9186-470e-b84e-51c2eb7318ca
dc.identifier.urihttps://hdl.handle.net/10125/109046
dc.relation.ispartofProceedings of the 58th 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.subjectSimulation Modeling, Artificial Intelligence and Digital Twins for Decision Making in Production and Logistics
dc.subjectmachine learning, material flow simulation, metaheuristics, metamodeling, optimization
dc.titleMetamodel-based Simulation Optimization Using Machine Learning for Solving Production Planning Problems in the Automotive Industry
dc.typeConference Paper
dc.type.dcmiText
prism.startingpage1675

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
0166.pdf
Size:
936.58 KB
Format:
Adobe Portable Document Format
Download

Collections

Simulation Modeling, Artificial Intelligence and Digital Twins for Decision Making in Production and Logistics