Developing a Decision Support System for Integrated Decision-Making in Purchasing and Scheduling under Lead Time Uncertainty

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dc.contributor.authorRolf, Benjamin
dc.contributor.authorReggelin, Tobias
dc.contributor.authorLang, Sebastian
dc.contributor.authorGalka, Stefan
dc.date.accessioned2021-12-24T17:35:18Z
dc.date.available2021-12-24T17:35:18Z
dc.date.issued2022-01-04
dc.description.abstractDecision-making in supply chain management is complex because of the relations between planning tasks from different stages and planning levels. Uncertainties such as unpredictable supplier lead times and supply chain disruptions further complicate decision-making. Considering the case study of a company in printed circuit board assembly, a three-level concept is proposed that includes a decision support system. The global single-source supply network is characterized by highly variable lead times. Hence, the company maintains high inventory levels to prevent running out of stock. The decision support system considers the purchasing and scheduling decision problems in an integrated way. The prototypical implementation of the purchasing algorithm uses a genetic algorithm that recommends reorder days and order quantities using a simulation model. In addition, it evaluates the risks of the recommended solution by calculating the probability of stockouts for each order cycle.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2022.247
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/79579
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.subjectSimulation Modeling and Digital Twins for Decision Making in the Age of Industry 4.0
dc.subjectdecision support system
dc.subjectsimulation
dc.subjectsupply chain optimization
dc.subjectpurchasing
dc.subjectcyber-physical system
dc.titleDeveloping a Decision Support System for Integrated Decision-Making in Purchasing and Scheduling under Lead Time Uncertainty
dc.type.dcmitext

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Simulation Modeling and Digital Twins for Decision Making in the Age of Industry 4.0