Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/188774 
Erscheinungsjahr: 
2016
Quellenangabe: 
[Journal:] Journal of Industrial Engineering and Management (JIEM) [ISSN:] 2013-0953 [Volume:] 9 [Issue:] 2 [Publisher:] OmniaScience [Place:] Barcelona [Year:] 2016 [Pages:] 359-373
Verlag: 
OmniaScience, Barcelona
Zusammenfassung: 
Purpose: Propose a modeling and analysis methodology based on the combination of Bayesian networks and Petri networks of the reverse logistics integrated the direct supply chain. Design/methodology/approach: Network modeling by combining Petri and Bayesian network. Findings: Modeling with Bayesian network complimented with Petri network to break the cycle problem in the Bayesian network. Research limitations/implications: Demands are independent from returns. Practical implications: Model can only be used on nonperishable products. Social implications: Legislation aspects: Recycling laws; Protection of environment; Client satisfaction via after sale service. Originality/value: Bayesian network with a cycle combined with the Petri Network.
Schlagwörter: 
reverse logistics
processes
graphical modeling
uncertainty
Petri network
Bayesian network
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