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SUPPLY CHAIN RISK MANAGEMENT BY MONTE CARLO METHOD

cris.lastimport.scopus2024-09-19T01:31:30Z
dc.abstract.enIn this paper, the conceptual model of risk-based cost estimation for completing tasks within supply chain is presented. This model is a hybrid. Its main unit is based on Monte Carlo Simulation (MCS). Due to the fact that the important and difficult to evaluate input information is vector of risk-occur probabilities the use of artificial intelligence method was proposed. The model assumes the use of fuzzy logic or artificial neural networks – depending on the availability of historical data. The presented model could provide support to managers in making valuation decisions regarding various tasks in supply chain management.
dc.affiliationTransportu i Informatyki
dc.contributor.authorTomasz Rymarczyk
dc.contributor.authorGrzegorz Kłosowski
dc.date.accessioned2024-05-07T11:52:48Z
dc.date.available2024-05-07T11:52:48Z
dc.date.issued2017
dc.identifier.doi10.5604/01.3001.0010.7244
dc.identifier.issn2083-0157
dc.identifier.issn2391-6761
dc.identifier.urihttps://repo.akademiawsei.eu/handle/item/282
dc.languageen
dc.pbn.affiliationinformation and communication technology
dc.relation.ispartofInformatics Control Measurement in Economy and Environment Protection
dc.rightsCC-BY-SA
dc.subject.enproject management
dc.subject.endecision support systems
dc.subject.enneural networks
dc.subject.enfuzzy logic
dc.titleSUPPLY CHAIN RISK MANAGEMENT BY MONTE CARLO METHOD
dc.typeReviewArticle
dspace.entity.typePublication
oaire.citation.issue4
oaire.citation.volume7